New energy power rapid charging power supply system

Abstract

The invention discloses a new energy power quick charging power supply system, which belongs to the technical field of new energy charging, and comprises an input interface power supply monitoring module for judging whether the working mode of an interface circuit needs to be adjusted based on preprocessed input interface power supply monitoring data; the charging mode control module is used for adjusting the working mode of the interface circuit; the battery pack operation state data acquisition module is used for acquiring battery pack operation state data and judging whether the battery pack operation state is abnormal or not based on the battery pack operation state data; and the battery pack health data acquisition module is used for judging the health state of the battery pack based on the battery pack health monitoring data, estimating the residual electric quantity of the battery pack based on an ampere-hour integral method if the health state is normal, and giving an alarm based on a set alarm mechanism if the health state is abnormal. Through precise monitoring and intelligent control, the charging mode is dynamically adjusted, charging safety can be guaranteed in real time, the charging efficiency is remarkably improved, and the service life of the battery is prolonged.

Description

Technical Field

[0001] The present invention belongs to the field of new energy charging technology, and specifically relates to a new energy power fast charging power supply system. Background Art

[0002] New energy power rapid charging systems are a key technology for providing efficient, fast, and safe charging for new energy power equipment. With the widespread adoption of new energy vehicles, power storage systems, and other new energy applications, the performance of charging technology directly impacts the operational efficiency and user experience of these devices. The core goal of this system is to provide a stable charging power source that adapts to various types of new energy power equipment and meets the demands for high power, fast response, and safe charging.

[0003] New energy power rapid charging systems can be applied in a variety of fields, including electric vehicles, high-speed rail transit, new energy ships, and drones. These systems typically involve charging power management, battery compatibility optimization, intelligent control strategies, and safety mechanisms to ensure efficient charging of new energy power equipment and extend battery life. Furthermore, these systems can be integrated with renewable energy sources such as solar and wind power to achieve efficient green energy utilization, improve energy efficiency, and promote the development of new energy technologies.

[0004] However, existing technologies suffer from inaccurate input power monitoring and insufficient monitoring of battery pack operating status. This leads to limitations in improving charging efficiency and ensuring battery safety. These issues make it difficult to ensure stable power input and detect and address battery pack anomalies in a timely manner, potentially posing safety risks and impacting battery life and system reliability. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a new energy power fast charging power supply system. Through precise monitoring and intelligent control, it dynamically adjusts the charging mode, which can ensure charging safety in real time, significantly improve charging efficiency and extend battery life.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: New energy power fast charging power system, including: An input interface power monitoring module is used to obtain input interface power monitoring data, pre-process the input interface power monitoring data, and determine whether the working mode of the interface circuit needs to be adjusted based on the pre-processed input interface power monitoring data; A charging mode control module is used to adjust the working mode of the interface circuit, including constant current charging mode, constant voltage charging mode and pulse charging mode; A battery pack operating status data acquisition module is used to obtain battery pack operating status data and determine whether there is any abnormality in the battery pack operating status based on the battery pack operating status data. If it is determined that there is no abnormality, monitoring will continue; if it is determined that there is an abnormality, charging will be stopped and battery pack health monitoring data will be acquired; The battery pack health data acquisition module is used to obtain battery pack health monitoring data and judge the health status of the battery pack based on the battery pack health monitoring data. If the health status is normal, the remaining battery power is estimated based on the ampere-hour integration method. If the health status is abnormal, an alarm is issued based on the set alarm mechanism.

[0007] Preferably, the specific process of determining whether the working mode of the interface circuit needs to be adjusted is as follows: Obtain the input interface power monitoring threshold stored in the database; Obtain the power monitoring data of the parameter input interface, including the parameter input power voltage, parameter input power frequency and parameter input power phase; Obtain the input interface power monitoring allowable deviation data, including the input power voltage allowable deviation value, the input power frequency allowable deviation value, and the input power phase allowable deviation value; Compare the input interface power monitoring data, the parameterized input interface power monitoring data and the input interface power monitoring allowable deviation data to determine the input interface power rating coefficient. The input interface power monitoring data includes the input power voltage, the input power frequency and the input power phase. Compare the input interface power rating coefficient with the input interface power monitoring threshold to determine whether the input interface power rating coefficient is less than the input interface power monitoring threshold; If it is determined that the input interface power rating coefficient is less than the input interface power monitoring threshold, there is no need to adjust the working mode of the interface circuit; If it is determined that the input interface power rating coefficient is not less than the input interface power monitoring threshold, the working mode of the interface circuit needs to be adjusted.

[0008] Preferably, the input interface power monitoring allowable deviation data is obtained, and the specific process is as follows: Obtain data on the impact of input interface power supply deviations, including load changes, line losses, and electromagnetic interference; Acquire an input interface power supply deviation impact matching data set stored in a database, including a plurality of input interface power supply deviation impact matching data, where the input interface power supply deviation impact matching data includes a load change matching value, a line loss matching value, and an electromagnetic interference matching value; Compare the input interface power deviation impact data with the input interface power deviation impact matching data stored in the database one by one to determine the power deviation comparison value of each input interface; The input interface power deviation impact matching data corresponding to the minimum input interface power deviation comparison value is determined, and the input interface power monitoring allowable deviation data corresponding to the input interface power deviation impact matching data is obtained from a database based on the input interface power deviation impact matching data.

[0009] Preferably, the calculation formula of the input interface power rating coefficient is: ; Where, is the input interface power rating coefficient, To access the power supply voltage, To determine the input power voltage, To access the power supply voltage allowable deviation value, To access the power frequency, To determine the power supply frequency, The allowable deviation value of the power supply frequency is To access the power phase, To determine the power supply phase, The allowable deviation value of the power supply phase.

[0010] Preferably, the calculation formula of the input interface power supply deviation comparison value is: ; Where, is the input interface power supply deviation comparison value, For load changes, is the load change matching value, is the line loss, is the line loss matching value, For electromagnetic interference, is the electromagnetic interference matching value.

[0011] Preferably, the specific process of determining whether the battery pack operating state is abnormal based on the battery pack operating state data is as follows: Obtain battery pack operating status parameter data, including parameterized harmonic content, parameterized power factor, and parameterized inrush current; Obtain the allowable deviation data of the battery pack operating status, including the allowable deviation value of the power factor and the allowable deviation value of the inrush current; Determining a battery pack operating state evaluation coefficient based on battery pack operating state data, battery pack operating state parameter data, and battery pack operating state allowable deviation data, where the battery pack operating state data includes harmonic content, power factor, and inrush current; If the battery pack operating state evaluation coefficient is greater than the battery pack operating state evaluation threshold stored in the database, it is determined that the battery pack operating state is abnormal; If it is determined that the battery pack operating state evaluation coefficient is not greater than the battery pack operating state evaluation threshold stored in the database, it is determined that there is no abnormality in the battery pack operating state.

[0012] Preferably, the battery pack operating state allowable deviation data is obtained, and the specific process is as follows: Obtain data on the impact of operational status deviations, including ambient temperature changes and power supply voltage fluctuations; Acquire an operating state deviation impact matching data set stored in a database, including a plurality of operating state deviation impact matching data, the operating state deviation impact matching data including an ambient temperature change matching value and a power supply voltage fluctuation matching value; Compare the running state deviation impact data with each running state deviation impact matching data stored in the database one by one to determine each running state deviation comparison value; The operating state deviation impact matching data corresponding to the minimum operating state deviation comparison value is determined, and corresponding battery pack operating state allowable deviation data is acquired from a database based on the operating state deviation impact matching data.

[0013] Preferably, the health status of the battery pack is determined based on the battery pack health monitoring data, and the specific process is as follows: Obtain battery pack health monitoring parameter data, including parameter battery internal resistance data, parameter battery capacity attenuation data and parameter battery cycle life data; Obtain the allowable deviation data of battery pack health monitoring, including the allowable deviation value of battery internal resistance data and the allowable deviation value of battery capacity attenuation data; Determine the battery pack health monitoring assessment coefficient based on battery pack health monitoring data, battery pack health monitoring parameter data and battery pack health monitoring allowable deviation data. The battery pack health monitoring data includes battery internal resistance data, battery capacity attenuation data and battery cycle life data; If the battery pack health monitoring assessment coefficient is determined to be greater than the battery pack health monitoring assessment threshold stored in the database, it is determined that the battery pack health status is abnormal; If it is determined that the battery pack health monitoring assessment coefficient is not greater than the battery pack health monitoring assessment threshold stored in the database, it is determined that there is no abnormality in the battery pack health status.

[0014] Preferably, the battery pack health monitoring allowable deviation data is obtained, and the specific process is as follows: Obtain health monitoring deviation impact data, including battery charge and discharge status and self-discharge rate; Obtaining a health monitoring deviation impact matching data set stored in a database, including multiple health monitoring deviation impact matching data, where the health monitoring deviation impact matching data includes a battery charge and discharge state matching value and a self-discharge rate matching value; Compare the health monitoring deviation impact data with each health monitoring deviation impact matching data stored in the database one by one to determine each health monitoring deviation comparison value; Determine health monitoring deviation impact matching data corresponding to the minimum health monitoring deviation comparison value, and obtain corresponding battery pack health monitoring allowable deviation data from a database based on the health monitoring deviation impact matching data.

[0015] Preferably, the remaining capacity of the battery pack is estimated based on the ampere-hour integration method, and the specific process is as follows: The battery charge change is calculated by integrating the battery charge and discharge current: ; Where, is the remaining power at time t, is the remaining battery power at the initial moment, is the battery charge and discharge current, is the rated capacity of the battery.

[0016] The present invention has the following beneficial effects: Through precise monitoring and intelligent control of the entire charging process, the present invention dynamically adjusts the operating mode of the interface circuit according to the input power status, ensuring the stability of the power input while optimizing charging efficiency through the control of multiple charging modes. It can acquire battery pack operating status data in real time, accurately identify abnormal conditions, and promptly terminate charging when an abnormality occurs, thereby improving charging safety and battery life. This solves the problems commonly encountered in existing technologies for new energy power fast-charging power systems, such as inaccurate input power monitoring and insufficient monitoring of battery pack operating status.

[0017] The present invention has high charging efficiency and achieves fast charging by dynamically adjusting the charging mode through precise monitoring and intelligent control of power input; it has strong safety by monitoring the operating status of the battery pack in real time, promptly discovering and handling abnormal situations, and avoiding safety hazards caused by battery abnormalities; it extends battery life by reducing the operating time of the battery in poor conditions and reducing battery loss through precise monitoring and intelligent control; it has good compatibility and is adaptable to different types of new energy power equipment, meeting the needs of high power, fast response, and safe charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of the new energy power fast charging power supply system of the present invention. DETAILED DESCRIPTION

[0019] The embodiments of the present invention are further described below with reference to the accompanying drawings: Example 1: Figure 1 As shown, the new energy power fast charging power system includes: An input interface power monitoring module is used to obtain input interface power monitoring data, pre-process the input interface power monitoring data, and determine whether the working mode of the interface circuit needs to be adjusted based on the pre-processed input interface power monitoring data; A charging mode control module is used to adjust the working mode of the interface circuit, including constant current charging mode, constant voltage charging mode and pulse charging mode; A battery pack operating status data acquisition module is used to obtain battery pack operating status data and determine whether there is any abnormality in the battery pack operating status based on the battery pack operating status data. If it is determined that there is no abnormality, monitoring will continue; if it is determined that there is an abnormality, charging will be stopped and battery pack health monitoring data will be acquired; The battery pack health data acquisition module is used to obtain battery pack health monitoring data and judge the health status of the battery pack based on the battery pack health monitoring data. If the health status is normal, the remaining battery power is estimated based on the ampere-hour integration method. If the health status is abnormal, an alarm is issued based on the set alarm mechanism.

[0020] In the input interface power monitoring module, based on the pre-processed input interface power monitoring data, it is determined whether the working mode of the interface circuit needs to be adjusted. The specific process is as follows: Obtain the input interface power monitoring threshold stored in the database; Obtain the power monitoring data of the parameter input interface, including the parameter input power voltage, parameter input power frequency and parameter input power phase; Obtain the input interface power monitoring allowable deviation data, including the input power voltage allowable deviation value, the input power frequency allowable deviation value, and the input power phase allowable deviation value; Compare the input interface power monitoring data, the parameterized input interface power monitoring data and the input interface power monitoring allowable deviation data to determine the input interface power rating coefficient. The input interface power monitoring data includes the input power voltage, the input power frequency and the input power phase. Compare the input interface power rating coefficient with the input interface power monitoring threshold to determine whether the input interface power rating coefficient is less than the input interface power monitoring threshold; If it is determined that the input interface power rating coefficient is less than the input interface power monitoring threshold, there is no need to adjust the working mode of the interface circuit; If it is determined that the input interface power rating coefficient is not less than the input interface power monitoring threshold, the working mode of the interface circuit needs to be adjusted.

[0021] The calculation formula for the input interface power rating coefficient is: ; Where, is the input interface power rating coefficient, To access the power supply voltage (Volts), To determine the input power supply voltage (V), is the allowable deviation value of the input power supply voltage (Volts), is the incoming power frequency (Hz), To determine the incoming power frequency (Hz), is the allowable deviation value of the incoming power frequency (Hz), is the phase of the incoming power supply (radians), To determine the phase of the incoming power supply (radian), The allowable deviation value of the power supply phase (radians).

[0022] By monitoring the output voltage in real time and dynamically adjusting circuit parameters, the voltage output to the subsequent power conversion module remains stable within the set range, with fluctuation errors kept to a minimum, providing a solid foundation for stable system operation. This system can promptly detect discrepancies between the input interface power supply and the standard, ensuring stable and reliable input power to the charging system. This effectively prevents system failures caused by abnormal input power, improves the stability and reliability of the charging system, and ensures the safe and efficient operation of new energy power rapid charging systems. Furthermore, based on the judgment results, the interface circuit operating mode can be appropriately adjusted to extend the system life and optimize the charging process.

[0023] Obtain the input interface power monitoring allowable deviation data. The specific process is as follows: Obtain data on the impact of input interface power supply deviations, including load changes, line losses, and electromagnetic interference; Acquire an input interface power supply deviation impact matching data set stored in a database, including a plurality of input interface power supply deviation impact matching data, where the input interface power supply deviation impact matching data includes a load change matching value, a line loss matching value, and an electromagnetic interference matching value; Compare the input interface power deviation impact data with the input interface power deviation impact matching data stored in the database one by one to determine the power deviation comparison value of each input interface; The input interface power deviation impact matching data corresponding to the minimum input interface power deviation comparison value is determined, and the input interface power monitoring allowable deviation data corresponding to the input interface power deviation impact matching data is obtained from a database based on the input interface power deviation impact matching data.

[0024] The calculation formula for the input interface power supply deviation comparison value is: ; Where, is the input interface power supply deviation comparison value, is the load change (%), is the load change matching value (%), is the line loss (watts), is the line loss matching value (watt), is the electromagnetic interference (volts per meter), is the electromagnetic interference matching value (volts per meter).

[0025] Different charging devices, and even the same device at different charging stages, may require different power, resulting in varying loads. During power transmission, inherent line resistance may cause energy loss, leading to line losses. The charging environment can contain various sources of electromagnetic interference, such as nearby motors and communications equipment. This interference can affect parameters such as the voltage, frequency, and phase of the input power, causing fluctuations in monitored data. Allowing for deviations in these three parameters allows for better adaptation to diverse operating environments and actual conditions. Load variations, line losses, and the degree of electromagnetic interference may vary. By setting a tolerance, these variations can be tolerated within a certain range, eliminating the need to react to every minor change, thereby improving the system's adaptability and versatility.

[0026] In the battery pack operating status data acquisition module, whether the battery pack operating status is abnormal is determined based on the battery pack operating status data. The specific process is as follows: Obtain battery pack operating status parameter data, including parameterized harmonic content, parameterized power factor, and parameterized inrush current; Obtain the allowable deviation data of the battery pack operating status, including the allowable deviation value of the power factor and the allowable deviation value of the inrush current; Determining a battery pack operating state evaluation coefficient based on battery pack operating state data, battery pack operating state parameter data, and battery pack operating state allowable deviation data, where the battery pack operating state data includes harmonic content, power factor, and inrush current; If the battery pack operating state evaluation coefficient is greater than the battery pack operating state evaluation threshold stored in the database, it is determined that the battery pack operating state is abnormal; If it is determined that the battery pack operating state evaluation coefficient is not greater than the battery pack operating state evaluation threshold stored in the database, it is determined that there is no abnormality in the battery pack operating state.

[0027] The calculation formula for the battery pack operating status evaluation coefficient is: ; Where, is the battery pack operating status evaluation coefficient, is the harmonic content (dimensionless relative value), is the parameter harmonic content (dimensionless relative value), is the power factor (the ratio of real power to apparent power, dimensionless), is the parameterized power factor (dimensionless), is the allowable deviation value of power factor (dimensionless), is the surge current (amperes), To determine the surge current (ampere), is the allowable deviation value of surge current (ampere).

[0028] Promptly detect abnormal battery pack operation to avoid safety hazards such as overheating and short circuits caused by abnormal harmonic content, power factor, or inrush current, providing strong protection for equipment and personnel safety. Real-time and accurate monitoring of battery pack operating status can proactively identify potential problems and take action, reducing operational interruptions caused by abnormal conditions and ensuring stable system operation. By monitoring indicators such as power factor, inappropriate energy utilization can be promptly identified and adjusted for optimization, improving energy efficiency and reducing energy consumption.

[0029] Obtain the battery pack operating status allowable deviation data. The specific process is as follows: Obtain data on the impact of operational status deviations, including ambient temperature changes and power supply voltage fluctuations; Acquire an operating state deviation impact matching data set stored in a database, including a plurality of operating state deviation impact matching data, the operating state deviation impact matching data including an ambient temperature change matching value and a power supply voltage fluctuation matching value; Compare the running state deviation impact data with each running state deviation impact matching data stored in the database one by one to determine each running state deviation comparison value; The operating state deviation impact matching data corresponding to the minimum operating state deviation comparison value is determined, and corresponding battery pack operating state allowable deviation data is acquired from a database based on the operating state deviation impact matching data.

[0030] The calculation formula for the operating status deviation comparison value is: ; Where, is the running status deviation comparison value, is the ambient temperature change (°C), is the matching value of the ambient temperature change (℃), is the power supply voltage fluctuation (volts), is the power supply voltage fluctuation matching value (Volts). 、 、 、 Perform dimensionless processing.

[0031] In real-world scenarios, the ambient temperature of a battery pack is not constant. Temperature fluctuations directly affect its performance. For example, excessively high temperatures can accelerate battery aging and reduce capacity, while excessively low temperatures can increase the battery's internal resistance and reduce charge and discharge efficiency. Maintaining absolute stability in actual power supply operations is difficult. Factors such as grid load fluctuations, peak and off-peak periods, power line losses, and the startup and shutdown of nearby electrical equipment can all cause power supply voltage fluctuations. Allowing for a deviation in these two parameters allows for better adaptation to complex and changing operating environments. Different application scenarios may experience varying degrees of ambient temperature and power supply voltage fluctuations. By setting a tolerance, these variations can be tolerated within a certain range, rather than overreacting to every subtle change.

[0032] In the battery pack health data acquisition module, the health status of the battery pack is judged based on the battery pack health monitoring data. The specific process is as follows: Obtain battery pack health monitoring parameter data, including parameter battery internal resistance data, parameter battery capacity attenuation data and parameter battery cycle life data; Obtain the allowable deviation data of battery pack health monitoring, including the allowable deviation value of battery internal resistance data and the allowable deviation value of battery capacity attenuation data; Determine the battery pack health monitoring assessment coefficient based on battery pack health monitoring data, battery pack health monitoring parameter data and battery pack health monitoring allowable deviation data. The battery pack health monitoring data includes battery internal resistance data, battery capacity attenuation data and battery cycle life data; If the battery pack health monitoring assessment coefficient is determined to be greater than the battery pack health monitoring assessment threshold stored in the database, it is determined that the battery pack health status is abnormal; If it is determined that the battery pack health monitoring assessment coefficient is not greater than the battery pack health monitoring assessment threshold stored in the database, it is determined that there is no abnormality in the battery pack health status.

[0033] The calculation formula for the battery pack health monitoring assessment coefficient is: ; Where, is the battery pack health monitoring assessment coefficient, is the battery internal resistance data (ohm), To determine the battery internal resistance data (ohm), The allowable deviation value of the battery internal resistance data (ohm), is the battery capacity attenuation data (%), To determine the battery capacity attenuation data (%), is the allowable deviation value of battery capacity attenuation data (%), is the battery cycle life data (number of times, dimensionless), To determine the battery cycle life data (number of times, dimensionless).

[0034] Promptly detect abnormalities in the health of the battery pack, such as abnormally increased internal resistance or rapid capacity decay, effectively avoiding equipment failures and operational interruptions caused by battery pack health issues, ensuring the stable and reliable operation of equipment or systems that rely on battery pack power. By monitoring and evaluating key indicators such as battery internal resistance data, battery capacity decay data, and battery cycle life data, potential health risks of the battery pack can be identified early, allowing for proactive maintenance, servicing, or replacement measures to prevent continued operation of the battery pack in an undesirable state, thereby extending the overall battery pack lifespan and reducing equipment operating costs.

[0035] Obtain the battery pack health monitoring tolerance data. The specific process is as follows: Obtain health monitoring deviation impact data, including battery charge and discharge status and self-discharge rate; Obtaining a health monitoring deviation impact matching data set stored in a database, including multiple health monitoring deviation impact matching data, where the health monitoring deviation impact matching data includes a battery charge and discharge state matching value and a self-discharge rate matching value; Compare the health monitoring deviation impact data with each health monitoring deviation impact matching data stored in the database one by one to determine each health monitoring deviation comparison value; Determine health monitoring deviation impact matching data corresponding to the minimum health monitoring deviation comparison value, and obtain corresponding battery pack health monitoring allowable deviation data from a database based on the health monitoring deviation impact matching data.

[0036] The calculation formula for the health monitoring deviation comparison value is: ; Where, is the health monitoring deviation comparison value, is the battery charge and discharge state (dimensionless relative value), is the battery charge and discharge state matching value (dimensionless relative value), is the self-discharge rate (dimensionless relative value), is the self-discharge rate matching value (dimensionless relative value).

[0037] In actual use, a battery's charge and discharge state constantly changes. Different application scenarios and device requirements can lead to differences in the rate, depth, and frequency of battery charge and discharge. Self-discharge is an inherent characteristic of batteries; even when unconnected to any load, the battery will slowly discharge due to internal chemical reactions. Allowing for variations in battery charge and discharge state and self-discharge rate allows for better adaptation to different battery types and complex, changing usage environments. By setting a tolerance, these variations can be accommodated within a certain range.

[0038] The remaining capacity of the battery pack is estimated based on the ampere-hour integration method. The specific process is as follows: The core goal of the remaining capacity (SOC) estimation is to accurately present the current remaining usable capacity of the battery. The ampere-hour integration method is the basis, and its logic is to calculate the change in capacity by integrating the battery charge and discharge current. Assuming that the initial time The remaining battery charge is (%), in the time interval The battery charge and discharge current is (Ampere), and calculate the battery charge change by integrating the battery charge and discharge current: ; Where, is the remaining power at time t (%), is the rated capacity of the battery (ampere-hours, converted to ampere-seconds for comparison with the integral term), and t is the time integral variable (seconds).

[0039] Continuously accumulate or deduct the amount of electricity during the charge and discharge process. For example, when charging, the current is positive, and the integration increases the SOC. When discharging, the current is negative, and the SOC decreases.

[0040] Example 2: Based on Example 1, the charging mode control module is further configured to adjust the charging mode according to the real-time temperature of the battery pack, specifically: When the battery pack temperature is lower than the preset low temperature threshold, the preheating function is activated, and charging will resume in the original mode after the temperature returns to the normal range; When the battery pack temperature is higher than the preset high temperature threshold, the charging power is reduced or charging is suspended to prevent battery overheating and damage; Temperature monitoring data is updated every 1-5 seconds to ensure that the charging mode can adapt to temperature changes in a timely manner.

[0041] The input interface power monitoring module is also used to monitor the harmonic content of the input power and trigger the corresponding filtering mechanism when the harmonic content exceeds the preset threshold to reduce the impact of harmonics on the charging process and improve charging efficiency and battery life.

[0042] When adjusting the charging mode, the charging mode control module also dynamically allocates the charging power of each battery cell according to the balanced charging requirements of the battery pack to ensure that each battery cell in the battery pack can be charged evenly, thereby further extending the service life of the battery pack.

Claims

1. New energy power fast charging power supply system, characterized by: include: An input interface power monitoring module is used to obtain input interface power monitoring data, pre-process the input interface power monitoring data, and determine whether the working mode of the interface circuit needs to be adjusted based on the pre-processed input interface power monitoring data; A charging mode control module is used to adjust the working mode of the interface circuit, including constant current charging mode, constant voltage charging mode and pulse charging mode; A battery pack operating status data acquisition module is used to obtain battery pack operating status data and determine whether there is any abnormality in the battery pack operating status based on the battery pack operating status data. If it is determined that there is no abnormality, monitoring will continue; if it is determined that there is an abnormality, charging will be stopped and battery pack health monitoring data will be acquired; The battery pack health data acquisition module is used to obtain battery pack health monitoring data and judge the health status of the battery pack based on the battery pack health monitoring data. If the health status is normal, the remaining battery power is estimated based on the ampere-hour integration method. If the health status is abnormal, an alarm is issued based on the set alarm mechanism.

2. The new energy power fast charging power supply system according to claim 1, characterized in that: Based on the pre-processed input interface power monitoring data, it is determined whether the working mode of the interface circuit needs to be adjusted. The specific process is as follows: Obtain the input interface power monitoring threshold stored in the database; Obtain the power monitoring data of the parameter input interface, including the parameter input power voltage, parameter input power frequency and parameter input power phase; Obtain the input interface power monitoring allowable deviation data, including the input power voltage allowable deviation value, the input power frequency allowable deviation value, and the input power phase allowable deviation value; Compare the input interface power monitoring data, the parameterized input interface power monitoring data and the input interface power monitoring allowable deviation data to determine the input interface power rating coefficient. The input interface power monitoring data includes the input power voltage, the input power frequency and the input power phase. Compare the input interface power rating coefficient with the input interface power monitoring threshold to determine whether the input interface power rating coefficient is less than the input interface power monitoring threshold; If it is determined that the input interface power rating coefficient is less than the input interface power monitoring threshold, there is no need to adjust the working mode of the interface circuit; If it is determined that the input interface power rating coefficient is not less than the input interface power monitoring threshold, the working mode of the interface circuit needs to be adjusted.

3. The new energy power fast charging power supply system according to claim 2, characterized in that: Obtain the input interface power monitoring allowable deviation data. The specific process is as follows: Obtain data on the impact of input interface power supply deviations, including load changes, line losses, and electromagnetic interference; Acquire an input interface power supply deviation impact matching data set stored in a database, including a plurality of input interface power supply deviation impact matching data, where the input interface power supply deviation impact matching data includes a load change matching value, a line loss matching value, and an electromagnetic interference matching value; Compare the input interface power deviation impact data with the input interface power deviation impact matching data stored in the database one by one to determine the power deviation comparison value of each input interface; The input interface power deviation impact matching data corresponding to the minimum input interface power deviation comparison value is determined, and the input interface power monitoring allowable deviation data corresponding to the input interface power deviation impact matching data is obtained from a database based on the input interface power deviation impact matching data.

4. The new energy power fast charging power supply system according to claim 2, characterized in that: The calculation formula for the input interface power rating coefficient is: ； Where, is the input interface power rating coefficient, To access the power supply voltage, To determine the input power voltage, To access the power supply voltage allowable deviation value, To access the power frequency, To determine the power supply frequency, The allowable deviation value of the power supply frequency is To access the power phase, To determine the power supply phase, The allowable deviation value of the power supply phase.

5. The new energy power fast charging power supply system according to claim 3, characterized in that: The calculation formula for the input interface power supply deviation comparison value is: ； Where, is the input interface power supply deviation comparison value, For load changes, is the load change matching value, is the line loss, is the line loss matching value, For electromagnetic interference, is the electromagnetic interference matching value.

6. The new energy power fast charging power supply system according to claim 1, characterized in that: Based on the battery pack operating status data, it is determined whether the battery pack operating status is abnormal. The specific process is as follows: Obtain battery pack operating status parameter data, including parameterized harmonic content, parameterized power factor, and parameterized inrush current; Obtain the allowable deviation data of the battery pack operating status, including the allowable deviation value of the power factor and the allowable deviation value of the inrush current; Determining a battery pack operating state evaluation coefficient based on battery pack operating state data, battery pack operating state parameter data, and battery pack operating state allowable deviation data, where the battery pack operating state data includes harmonic content, power factor, and inrush current; If the battery pack operating state evaluation coefficient is greater than the battery pack operating state evaluation threshold stored in the database, it is determined that the battery pack operating state is abnormal; If it is determined that the battery pack operating state evaluation coefficient is not greater than the battery pack operating state evaluation threshold stored in the database, it is determined that there is no abnormality in the battery pack operating state.

7. The new energy power fast charging power supply system according to claim 6, characterized in that: Obtain the battery pack operating status allowable deviation data. The specific process is as follows: Obtain data on the impact of operational status deviations, including ambient temperature changes and power supply voltage fluctuations; Acquire an operating state deviation impact matching data set stored in a database, including a plurality of operating state deviation impact matching data, the operating state deviation impact matching data including an ambient temperature change matching value and a power supply voltage fluctuation matching value; Compare the running state deviation impact data with each running state deviation impact matching data stored in the database one by one to determine each running state deviation comparison value; The operating state deviation impact matching data corresponding to the minimum operating state deviation comparison value is determined, and corresponding battery pack operating state allowable deviation data is acquired from a database based on the operating state deviation impact matching data.

8. The new energy power fast charging power supply system according to claim 1, characterized in that: The health status of the battery pack is determined based on the battery pack health monitoring data. The specific process is as follows: Obtain battery pack health monitoring parameter data, including parameter battery internal resistance data, parameter battery capacity attenuation data and parameter battery cycle life data; Obtain the allowable deviation data of battery pack health monitoring, including the allowable deviation value of battery internal resistance data and the allowable deviation value of battery capacity attenuation data; Determine the battery pack health monitoring assessment coefficient based on battery pack health monitoring data, battery pack health monitoring parameter data and battery pack health monitoring allowable deviation data. The battery pack health monitoring data includes battery internal resistance data, battery capacity attenuation data and battery cycle life data; If the battery pack health monitoring assessment coefficient is determined to be greater than the battery pack health monitoring assessment threshold stored in the database, it is determined that the battery pack health status is abnormal; If it is determined that the battery pack health monitoring assessment coefficient is not greater than the battery pack health monitoring assessment threshold stored in the database, it is determined that there is no abnormality in the battery pack health status.

9. The new energy power fast charging power supply system according to claim 8, characterized in that: Obtain the battery pack health monitoring tolerance data. The specific process is as follows: Obtain health monitoring deviation impact data, including battery charge and discharge status and self-discharge rate; Obtaining a health monitoring deviation impact matching data set stored in a database, including multiple health monitoring deviation impact matching data, where the health monitoring deviation impact matching data includes a battery charge and discharge state matching value and a self-discharge rate matching value; Compare the health monitoring deviation impact data with each health monitoring deviation impact matching data stored in the database one by one to determine each health monitoring deviation comparison value; Determine health monitoring deviation impact matching data corresponding to the minimum health monitoring deviation comparison value, and obtain corresponding battery pack health monitoring allowable deviation data from a database based on the health monitoring deviation impact matching data.

10. The new energy power fast charging power supply system according to claim 1, characterized in that: The remaining capacity of the battery pack is estimated based on the ampere-hour integration method. The specific process is as follows: The battery charge change is calculated by integrating the battery charge and discharge current: ； Where, is the remaining power at time t, is the remaining battery power at the initial moment, is the battery charge and discharge current, is the rated capacity of the battery.

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