New energy automobile charging management system

Abstract

The invention discloses a new energy automobile charging management system, and aims to improve the charging efficiency, prolong the service life of a battery and improve the user experience. The system comprises a battery monitoring module, a charging mode management module, an intelligent scheduling module, a remote control module, a safety protection module, a big data analysis module and a billing management module. The battery monitoring module collects data such as battery voltage, current and temperature in real time; the charging mode management module dynamically selects a fast, standard or slow charging mode according to the battery state and the user demand; the intelligent scheduling module optimizes a multi-vehicle charging sequence to realize reasonable resource allocation; the safety protection module provides overvoltage, overcurrent and temperature protection to ensure charging safety; the remote control module enables a user to monitor and adjust the charging state in real time. According to the invention, through intelligent charging management, resource configuration optimization, charging efficiency improvement, safety risk reduction in the charging process and battery life prolonging, convenient charging experience is provided for users.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile charging systems, and in particular to a new energy automobile charging management system. Background Art

[0002] As global environmental pollution becomes increasingly serious, developing clean energy and reducing greenhouse gas emissions have become issues of common concern to all countries. In this context, new energy vehicles, especially electric vehicles, have been widely promoted due to their zero emissions and low noise advantages. The rapid growth of the new energy vehicle market has driven the demand for charging infrastructure. However, the existing new energy vehicle charging management technology still has some technical bottlenecks and application challenges, which are mainly manifested in the following aspects:

[0003] Most existing charging systems use a single charging mode and lack the function of intelligent charging management based on the battery status. In the frequent fast charging mode, high current charging will cause the battery to heat up and increase the internal resistance, accelerate the battery capacity decay, and shorten the battery life. At the same time, the single charging mode cannot dynamically adjust the charging strategy according to the actual needs of the user and the battery status, resulting in low charging efficiency and difficulty in balancing efficiency and life protection.

[0004] In charging stations or parking lots, there are often multiple new energy vehicles queuing up to charge at the same time, but the existing charging management system lacks intelligent scheduling functions, making it difficult to reasonably allocate charging resources based on the power demand and charging priority of each vehicle. This may cause some vehicles that urgently need to charge to wait too long, while other vehicles with lower charging needs occupy charging pile resources, resulting in resource waste and reducing the overall utilization efficiency of the charging station.

[0005] The user monitoring and management functions of existing charging management systems are relatively limited. Users cannot view the charging status in real time during the charging process, and cannot remotely adjust the charging mode or terminate charging, which reduces the user experience to a certain extent. In addition, users usually cannot obtain charging history data and related information, which makes it inconvenient to manage the charging process and costs.

[0006] During the charging process, battery temperature, current, voltage and other parameters are easily affected by the external environment, especially in high or low temperature environments, the battery may be abnormal due to overheating or overcooling. The existing charging management system lacks a multi-level safety protection mechanism, making it difficult to respond in time and take effective safety protection measures in abnormal situations such as battery temperature, current overload or leakage, thereby increasing the safety risks of battery overheating, short circuit, leakage, etc.

[0007] Existing charging management systems are usually limited to simple monitoring of real-time data, lacking long-term analysis and utilization of charging data. Without incorporating historical data, charging patterns, and user behavior analysis into system management, it is impossible to predict the maintenance needs of charging equipment and the health status of batteries. In this way, equipment maintenance can only rely on regular inspections and cannot achieve predictive maintenance, which increases operating costs and may cause sudden equipment failures that affect the stability of charging services.

[0008] As the number of electric vehicles increases, the power grid faces greater load pressure during peak periods, especially during charging peaks at night or on holidays, which may cause local power grid overload. The existing charging management system lacks the ability to perceive and adjust the power grid load, and cannot make reasonable charging arrangements according to the peak and valley periods of electricity prices, which not only increases charging costs, but also wastes the grid's low-peak resources and fails to achieve efficient use of power resources.

[0009] In summary, the existing new energy vehicle charging management system has deficiencies in charging efficiency, intelligent scheduling, safety, user experience and big data analysis, and it is difficult to meet the growing market demand for new energy vehicles. Therefore, designing an intelligent, efficient, safe and user-friendly new energy vehicle charging management system to achieve flexible adjustment of charging modes, efficient scheduling of multiple vehicles, safety protection of the charging process and predictive maintenance of the system is of great significance for improving the user experience of new energy vehicles and the efficiency of charging infrastructure.

[0010] To this end, we urgently need to design a new energy vehicle charging management system to solve the above problems. Summary of the invention

[0011] The purpose of the present invention is to provide a new energy vehicle charging management system to address the deficiencies in the prior art and to solve the problems raised in the background technology.

[0012] To achieve the above object, the present invention provides the following technical solution: a new energy vehicle charging management system, the system comprising:

[0013] Battery monitoring module: used to monitor the battery voltage, current, temperature and health status in real time and obtain the real-time status data of the battery;

[0014] Charging mode management module: selects the charging mode according to the battery status data, including fast charging mode, standard charging mode and slow charging mode;

[0015] Intelligent scheduling module: used to manage the charging order of multiple vehicles and optimize the scheduling based on the charging pile load and vehicle charging priority;

[0016] Remote control module: allows users to remotely monitor and control the charging process through mobile devices;

[0017] Safety protection module: used to provide overvoltage protection, overcurrent protection, temperature protection and leakage protection functions;

[0018] Big data analysis module: used to collect and analyze data during the charging process to optimize scheduling strategies and provide predictive maintenance.

[0019] Furthermore, the charging mode management module selects the charging mode through the formula:

[0020] P max =I×V

[0021] Among them, P max is the maximum charging power, I is the battery current, and V is the battery voltage;

[0022] If the battery status meets the fast charging conditions, it enters the fast charging mode, otherwise it selects the standard charging or slow charging mode according to the charging requirements.

[0023] Furthermore, the charging mode management module controls the charging speed by adjusting the current during the charging process, and the charging power control equation is as follows:

[0024] P=I×V=Constant

[0025] In different charging modes, the value of I is adjusted so that the power P remains within the set range, where the P value is larger during fast charging and smaller during slow charging. Constant means that the charging power P is set to a constant value and remains unchanged throughout the charging process.

[0026] Furthermore, the intelligent scheduling module determines the charging order of the vehicles based on the following priority calculation formula:

[0027]

[0028] Among them, α is the priority weight coefficient, E min is the minimum power required by the vehicle, E current is the current power, T available The estimated available time of the vehicle. The larger the Priority value, the higher the charging priority of the vehicle.

[0029] Furthermore, the intelligent scheduling module gives priority to charging vehicles with higher urgency, and balances the charging time of other vehicles by delaying or reducing the power when the available power of the charging pile is insufficient.

[0030] Furthermore, the remote control module includes: a data display unit for displaying real-time charging status, charging voltage, current and battery temperature, and a control unit for receiving remote instructions from the user and sending them to the charging mode management module to switch and adjust the charging mode.

[0031] Furthermore, the safety protection module determines the real-time temperature T of the battery and the threshold temperature T threshold Compare, if the condition T>T is met threshold , then stop charging immediately and start cooling measures.

[0032] Furthermore, the leakage protection of the safety protection module detects the current difference ΔI between the ground wire and the charging device. When ΔI>I leak When the system immediately cuts off the charging circuit, I leak is the leakage current safety threshold.

[0033] Furthermore, the big data analysis module uses the following formula to predict the maintenance cycle of the equipment:

[0034]

[0035] Among them, MTTF is the mean time to failure, T operation is the normal operation time of each device, N failure is the number of failures. This module automatically generates maintenance suggestions based on historical data.

[0036] Furthermore, the charging management module calculates the charging fee according to the following formula:

[0037] Cost = E total ×C rate

[0038] Among them, E total is the total charge capacity, C rate The system dynamically calculates the charging cost and generates a bill based on the user's actual charging amount and the current electricity price.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The new energy vehicle charging management system of the present invention provides multiple charging modes, such as fast charging, standard charging and slow charging, and can dynamically adjust the charging strategy according to the real-time status of the battery and user needs. By intelligently selecting the appropriate charging mode, the heat generation of the battery and the loss of the battery caused by the increase of internal resistance can be reduced, and the battery life can be extended. In addition, by optimizing the charging process and charging power control, the charging efficiency is improved to meet the charging needs of users in different scenarios.

[0041] The system has a built-in intelligent scheduling module, which can reasonably allocate the charging order according to the charging needs and urgency of each new energy vehicle, ensuring that emergency vehicles are charged first and reducing waiting time. At the same time, when the charging pile load is high, the system can dynamically balance the charging power of each vehicle to prevent resource waste. This not only improves the resource utilization rate of the charging station, but also reduces the idle rate of charging equipment, providing a more efficient solution for scenarios where multiple vehicles are charged at the same time.

[0042] The system of the present invention has complete safety protection measures, including temperature monitoring, overvoltage protection, leakage detection, etc. It can promptly alarm and take protective measures under abnormal conditions to ensure the safety of the charging process. At the same time, through remote monitoring and control functions, users can view the charging status in real time, select the charging mode, and obtain cost estimates, which greatly improves the user experience. The system also has big data analysis and predictive maintenance functions, which can analyze the equipment status based on charging history data, make maintenance suggestions, reduce the risk of equipment failure, and reduce operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a system block diagram of a new energy vehicle charging management system proposed by the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] The following is combined with Figure 1 With reference to the accompanying drawings and a number of embodiments, specific embodiments of the present invention are described in detail.

[0046] Example 1: Intelligent charging management based on weather and environmental conditions

[0047] Under some extreme weather conditions, such as high or low temperatures, the charging performance and safety of the battery may be affected. This embodiment dynamically adjusts the strategy of the charging management system based on weather and ambient temperature to further improve charging efficiency and safety.

[0048] Environmental monitoring module: The system adds an environmental monitoring module to monitor the external ambient temperature. If the ambient temperature is detected to be higher than a certain set value (such as 35°C), the system automatically selects the slow charging mode to reduce the rate of battery temperature rise.

[0049] Temperature protection strategy: When the ambient temperature is low (such as below 5°C), the system will delay the start of charging and wait for the battery to preheat to an appropriate temperature before starting charging to avoid damage to battery performance due to low temperature.

[0050] Adjust charging power: When the ambient temperature is too high or too low, the system dynamically adjusts the power during charging to ensure that the temperature of the battery is stable during charging. For example, the system adjusts the charging current I so that P = I × V is always within a safe range.

[0051] Example 2: Multi-vehicle charging sharing scheduling

[0052] This embodiment is applicable to the scenario where multiple new energy vehicles share a charging pile in a charging station, and efficient charging of multiple vehicles can be achieved through intelligent scheduling to avoid waste of resources.

[0053] Intelligent scheduling optimization: When multiple vehicles are waiting to charge at the same time, the intelligent scheduling module calculates the priority and arranges the charging order based on the power status, charging demand and expected departure time of each vehicle. Charging priority strategy: The priority calculation formula is as follows:

[0054]

[0055] Among them, α is the priority weight coefficient, E min is the minimum power required by the vehicle, E current is the current power, T available The estimated available time for the vehicle. Dynamic adjustment strategy: When a vehicle is fully charged or the power reaches the set target, the system automatically switches to the next high-priority vehicle for charging to ensure efficient use of the charging pile.

[0056] Energy balance: When the load on the charging pile approaches the upper limit, the system will ensure that the charging pile operates within a safe load range by reducing the charging power of non-emergency vehicles or temporarily interrupting the charging of low-priority vehicles.

[0057] Example 3: Personalized charging mode based on user needs

[0058] This embodiment provides a personalized charging management method based on user needs, and users can select a suitable charging mode according to their travel plans through the App.

[0059] Demand analysis module: Users input information such as travel time, distance, and vehicle charging requirements through the App. The system automatically calculates the required power and recommends the corresponding charging mode.

[0060] Fast charging mode: If the user needs fast charging, the system will prioritize high-power charging and determine the appropriate charging current I based on the vehicle's current battery voltage and current to keep P = I × V within the fast charging range.

[0061] Energy-saving charging mode: If the user plans to park for a long time, the system recommends slow charging mode, charging with low current to reduce the electrochemical loss of the battery, thereby extending the battery life.

[0062] Smart recommendation: The system makes personalized recommendations based on historical charging records and user preferences. For example, if the user selects slow charging multiple times, the system will automatically recommend energy-saving charging mode.

[0063] Example 4: Remote monitoring and abnormal alarm function

[0064] This embodiment mainly describes the functions of the remote control module. Users can monitor the charging status at any time through the mobile app or PC during the charging process and receive alarm information when abnormal conditions occur. Real-time data monitoring: Users can view real-time battery voltage, current, charging power, temperature and other information through the app. All data is presented in charts for easy understanding by users.

[0065] Remote control function: Users can switch charging modes or terminate charging remotely. For example, when users find that the battery temperature is high, they can remotely switch the charging mode to slow charging to reduce the temperature rise rate.

[0066] Abnormal alarm: During the charging process, if the temperature or current exceeds the set safety threshold, the system will automatically stop charging and send an abnormal alarm notification to the user. The notification information is sent simultaneously through the App and SMS to ensure that the user is informed in time.

[0067] Real-time fault feedback: If a charging fault occurs (such as leakage or short circuit), the system will immediately cut off the power supply and record the fault information. Users can view the cause of the fault through the App and contact maintenance personnel for repair.

[0068] Example 5: Charging bill and billing management

[0069] This embodiment mainly describes the implementation of the billing management module. By automatically generating bills and multiple payment methods, the charging fee settlement process for users is simplified.

[0070] Dynamic billing: The system charges according to the current electricity price C rate and the user's charge E total Dynamically calculate the charging fee, the fee formula is as follows:

[0071] Cost = E total ×C rate

[0072] Bill generation: After charging is completed, the system automatically generates a bill, which includes detailed information such as charging time, total charging amount, electricity price per unit and total cost. Users can view and download the electronic bill on the App.

[0073] Multiple payment methods: The system supports multiple payment methods, including mobile payment, credit card payment, and prepaid recharge, etc. Users can choose the appropriate payment method for settlement.

[0074] Cost estimation: Before charging begins, the system can generate an estimated cost based on the charging mode selected by the user and the estimated charging time to help the user choose a reasonable charging method.

[0075] Example 6: Big data analysis and predictive maintenance

[0076] This embodiment introduces the long-term maintenance and optimization of the system through the big data analysis module. Data collection and storage: During each charging process, the system collects data such as charging current, voltage, temperature, charging time, battery health status, etc. and stores them in the cloud.

[0077] Predictive maintenance: Based on information such as failure time and charging frequency, the system calculates the mean time to failure (MTTF) of the equipment. The calculation formula is:

[0078]

[0079] Among them, T operation N is the normal operation time of the equipment, failure is the number of failures. Based on this, the system predicts the maintenance time of the equipment and sends maintenance suggestions to the management personnel.

[0080] Charging behavior analysis: The system analyzes peak charging periods and user preferences based on the user's charging habits, providing a basis for the scheduling and optimization of subsequent charging piles. For example, during peak charging periods (such as evening peaks), the system will increase the number of fast charging piles.

[0081] Charging efficiency optimization: Based on historical charging data analysis, the system compares the efficiency of each charging mode and continuously optimizes the charging power control algorithm to improve charging efficiency and extend battery life.

[0082] Example 7: Intelligent charging management based on grid load optimization

[0083] This embodiment describes that when the grid load is at a peak or valley, the system optimizes the use of grid resources by intelligently regulating the charging power, helping to reduce the load pressure during peak periods and efficiently utilizing power resources during valley periods.

[0084] Grid load monitoring module: The system integrates a grid load monitoring module, which receives grid load data in real time.

[0085] When it detects that the grid is at peak load, the system automatically reduces the power output of the charging pile; during low load periods, the system increases the charging power to take advantage of lower electricity prices and more abundant power resources.

[0086] Time-of-use electricity price management: The billing management module supports the time-of-use electricity price function and adjusts the charging fee according to different time periods.

[0087] During off-peak hours (such as late at night), the system automatically switches to economic mode and provides charging services at a lower electricity price, encouraging users to choose to charge during off-peak hours and reduce peak electricity consumption pressure.

[0088] Intelligent power regulation: The system dynamically adjusts the charging power P according to the grid load condition. When the grid load is high, the charging power formula is:

[0089] P=I×V×β

[0090] Where β is the load factor (0<β<1), which is used to adjust the charging power. The system adjusts the β value according to the load of the power grid and controls the output of the charging power to achieve load balance.

[0091] User notification and suggestions: During peak load periods, the system will notify users and recommend charging during off-peak hours to reduce charging costs.

[0092] Users can view the time-of-use electricity price list in the App and choose a suitable charging time period.

[0093] Example 8: Charging management based on battery life optimization

[0094] This embodiment aims to extend the battery life of new energy vehicles, and is particularly suitable for users or shared vehicle management companies who want to protect the battery to the greatest extent. Through precise charging control and temperature control measures, the loss of the battery during the charging process is reduced.

[0095] Battery life management module: The system has added a battery life management module to evaluate the current condition of the battery by collecting the battery's state of health (SoH) and historical charging data. This module works in conjunction with the charging mode management module to select the most appropriate charging mode to protect battery life.

[0096] Charging rate control: While ensuring charging efficiency, the system adopts a low current slow charging strategy. The charging power control formula is:

[0097] P=I×V=Constant (Low speed mode)

[0098] Among them, P is the set small power value, and I is a lower charging current to maintain a slower charging rate. This method is suitable for use in scenarios where the battery life is low or a longer life is required.

[0099] Temperature monitoring and cooling mechanism: During the charging process, the system monitors the battery temperature in real time.

[0100] When the temperature approaches the set upper limit, the system automatically reduces the charging current, slows down the temperature rise, or starts cooling equipment (such as fans or liquid cooling devices) to lower the battery temperature and avoid accelerated battery aging due to high temperature.

[0101] Dynamic battery life prediction: The system calculates the battery state of health (SoH) based on charging history data and the battery life decay curve using a formula to provide an estimate of the remaining service life:

[0102]

[0103] Among them, C current is the current battery capacity, C initial is the initial capacity of the battery.

[0104] The system provides users with battery maintenance or replacement suggestions based on the changing trend of SoH.

[0105] Intelligent user reminder: When the system detects that the battery health status (SoH) is lower than the set threshold, the system will remind the user through the App and recommend the use of low-speed charging mode to extend battery life. The system will also regularly push battery maintenance tips and charging suggestions to help users effectively manage battery life.

[0106] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in the field. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A new energy vehicle charging management system, characterized in that: The system includes: Battery monitoring module: used to monitor the battery voltage, current, temperature and health status in real time and obtain the real-time status data of the battery; Charging mode management module: selects the charging mode according to the battery status data, including fast charging mode, standard charging mode and slow charging mode; Intelligent scheduling module: used to manage the charging order of multiple vehicles and optimize the scheduling based on the charging pile load and vehicle charging priority; Remote control module: allows users to remotely monitor and control the charging process through mobile devices; Safety protection module: used to provide overvoltage protection, overcurrent protection, temperature protection and leakage protection functions; Big data analysis module: used to collect and analyze data during the charging process to optimize scheduling strategies and provide predictive maintenance.

2. A new energy vehicle charging management system according to claim 1, characterized in that: The charging mode management module selects the charging mode through the formula: P max =I×V Among them, P max is the maximum charging power, I is the battery current, and V is the battery voltage; If the battery status meets the fast charging conditions, it enters the fast charging mode, otherwise it selects the standard charging or slow charging mode according to the charging requirements.

3. A new energy vehicle charging management system according to claim 2, characterized in that: The charging mode management module controls the charging speed by adjusting the current during the charging process, and its charging power control equation is as follows: P=I×V=Constant In different charging modes, the value of I is adjusted so that the power P remains within the set range, where the P value is larger during fast charging and smaller during slow charging. Constant means that the charging power P is set to a constant value and remains unchanged throughout the charging process.

4. A new energy vehicle charging management system according to claim 1, characterized in that: The intelligent scheduling module determines the charging order of the vehicles based on the following priority calculation formula: Among them, α is the priority weight coefficient, E min is the minimum power required by the vehicle, E current is the current power, T available The estimated available time of the vehicle. The larger the Priority value, the higher the charging priority of the vehicle.

5. A new energy vehicle charging management system according to claim 4, characterized in that: The intelligent scheduling module gives priority to charging vehicles with higher urgency, and balances the charging time of other vehicles by delaying or reducing the power when the available power of the charging pile is insufficient.

6. A new energy vehicle charging management system according to claim 1, characterized in that: The remote control module includes: a data display unit for displaying real-time charging status, charging voltage, current and battery temperature, and a control unit for receiving remote instructions from users and sending them to the charging mode management module to switch and adjust the charging mode.

7. A new energy vehicle charging management system according to claim 1, characterized in that: The safety protection module uses the real-time temperature T of the battery and the threshold temperature T threshold Compare, if the condition T>T is met threshold , then stop charging immediately and start cooling measures.

8. A new energy vehicle charging management system according to claim 7, characterized in that: The leakage protection of the safety protection module detects the current difference ΔI between the ground wire and the charging device. When ΔI>I leak When the system immediately cuts off the charging circuit, I leak is the leakage current safety threshold.

9. A new energy vehicle charging management system according to claim 1, characterized in that: The big data analysis module uses the following formula to predict the maintenance cycle of equipment: Among them, MTTF is the mean time to failure, T operation is the normal operation time of each device, N failure is the number of failures. This module automatically generates maintenance suggestions based on historical data.

10. The charging management system according to claim 1, characterized in that: The charging management module calculates the charging fee according to the following formula: Cost=E total ×C rate Among them, E total is the total charge capacity, C rate The system dynamically calculates the charging cost and generates a bill based on the user's actual charging amount and the current electricity price.

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