Electric two-wheeled vehicle intelligent fast charging system, method, device and equipment

Abstract

The application discloses an electric two-wheeled vehicle intelligent fast charging system, method, device and equipment, which is capable of dynamically adjusting the charging power according to the real-time load rate of the power grid, significantly reducing the impact on the power grid when the public charging pile is concentratedly fast charged, improving the operation stability of the power grid, and adaptively matching the battery state and the environmental condition, reducing the damage of the high-residual-charge and low-health-degree battery in the fast charging process, and prolonging the service life of the battery. Meanwhile, the target charging power is determined through the collaborative calculation of the three coefficients and the preset charging basic power, effectively realizing the multi-objective balance of the fast charging efficiency, the power grid safety and the battery protection, and adapting to the application requirements of the fast charging popularization of the electric two-wheeled vehicle and the concentrated layout of the charging pile.

Description

Technical Field

[0001] This application relates to the field of two-wheeled vehicle charging, and in particular to an intelligent fast charging system, method, apparatus and equipment for electric two-wheeled vehicles. Background Technology

[0002] Existing fast charging systems for electric two-wheelers mostly employ single-parameter control, such as adjusting charging power solely based on the remaining battery capacity. However, with the widespread adoption of fast charging for electric two-wheelers and the centralized deployment of public charging stations, there is a risk of impacting the power grid. Directly limiting charging power, on the other hand, defeats the core purpose of promoting fast charging. Therefore, how to ensure fast charging efficiency while preventing grid impact and maintaining grid stability has become a critical issue that urgently needs to be addressed. Summary of the Invention

[0003] This application aims to propose an intelligent fast charging system, method, device, and equipment for electric two-wheeled vehicles, which can effectively balance fast charging efficiency and power grid stability.

[0004] According to a first aspect embodiment of the present application, the intelligent fast charging system for electric two-wheeled vehicles includes: An ambient temperature acquisition unit is used to acquire the real-time ambient temperature of the managed area. The power grid data acquisition unit is used to acquire the real-time load rate of the power grid in the managed area; The battery status acquisition unit is used to determine the remaining battery power and battery health in two-wheeled vehicles connected to a charging station. The main control unit is electrically connected to the ambient temperature acquisition unit, the power grid data acquisition unit, and the battery status acquisition unit, respectively. It is used to receive real-time ambient temperature, real-time power grid load rate, remaining power, and battery health. It determines the temperature compensation coefficient based on the real-time ambient temperature, the power grid load compensation coefficient based on the real-time power grid load rate, and the correction coefficient based on the remaining power and battery health. Finally, it determines the target charging power based on the preset charging base power, temperature compensation coefficient, power grid load compensation coefficient, and correction coefficient.

[0005] The intelligent fast charging method for electric two-wheeled vehicles according to the second aspect of this application, applied to the intelligent fast charging system for electric two-wheeled vehicles as described in the first aspect, includes: Obtain real-time ambient temperature, real-time grid load rate, remaining power, and battery health; The temperature compensation coefficient is determined based on the real-time ambient temperature, and the real-time ambient temperature is positively correlated with the temperature compensation coefficient. The power grid load compensation coefficient is determined based on the real-time power grid load rate, and the real-time power grid load rate is negatively correlated with the power grid load compensation coefficient. The correction coefficient is determined based on the remaining power and battery health. The remaining power is negatively correlated with the correction coefficient, while the battery health is positively correlated with the correction coefficient. The target charging power is determined based on the preset base charging power, temperature compensation coefficient, grid load compensation coefficient, and correction coefficient. Adjust the real-time charging power of the charging pile to the electric two-wheeler according to the target charging power.

[0006] The intelligent fast charging device for electric two-wheeled vehicles according to a third aspect of this application is applied to the intelligent fast charging system for electric two-wheeled vehicles as described in the first aspect embodiment. The intelligent fast charging device for electric two-wheeled vehicles includes: The parameter acquisition module is used to acquire real-time ambient temperature, real-time grid load rate, remaining power, and battery health. The first coefficient determination module is used to determine the temperature compensation coefficient based on the real-time ambient temperature. The real-time ambient temperature is positively correlated with the temperature compensation coefficient. The second coefficient determination module is used to determine the grid load compensation coefficient based on the real-time grid load rate. The real-time grid load rate is negatively correlated with the grid load compensation coefficient. The third coefficient determination module is used to determine the correction coefficient based on the remaining power and battery health. The remaining power is negatively correlated with the correction coefficient, while the battery health is positively correlated with the correction coefficient. The target power determination module is used to determine the target charging power based on the preset charging base power, temperature compensation coefficient, grid load compensation coefficient, and correction coefficient. The charging control module is used to adjust the real-time charging power of the charging pile to the electric two-wheeler according to the target charging power.

[0007] An electronic device according to a fourth aspect of this application includes: a processor and a memory storing computer program instructions; When the processor executes computer program instructions, it implements the intelligent fast charging method for electric two-wheeled vehicles as described in the second aspect embodiment.

[0008] The intelligent fast charging system, method, apparatus, and equipment for electric two-wheelers in this application integrate four parameters—ambient temperature, real-time grid load rate, remaining battery power, and battery health—for coordinated regulation. This allows for dynamic adjustment of charging power based on the real-time grid load rate, significantly reducing the impact on the grid during centralized fast charging at public charging stations and improving grid stability. Furthermore, it adapts to battery status and environmental conditions, minimizing damage to batteries with high remaining power and low health during fast charging and extending battery life. Simultaneously, by co-calculating the target charging power using three coefficients and a preset base charging power, it effectively achieves a multi-objective balance between fast charging efficiency, grid safety, and battery protection, thus meeting the application requirements for the promotion of fast charging for electric two-wheelers and the centralized deployment of charging stations.

[0009] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing this application. Attached Figure Description

[0010] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart of an intelligent fast charging method for electric two-wheeled vehicles according to an embodiment of this application; Figure 2 This is a flowchart illustrating the determination of the target charging power in the intelligent fast charging method for electric two-wheeled vehicles according to an embodiment of this application. Figure 3 This is a flowchart of a smart fast charging method for an electric two-wheeled vehicle according to another embodiment of this application. Detailed Implementation

[0011] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0012] In the description of this application, the use of terms such as "first," "second," etc., is for the purpose of distinguishing technical features only and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of the technical features indicated.

[0013] In the description of this application, it should be understood that the orientation descriptions, such as up, down, etc., are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0014] In the description of this application, it should be noted that, unless otherwise explicitly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0015] The technical solution of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are some embodiments of this application, not all embodiments.

[0016] One embodiment of this application provides an intelligent fast charging system for electric two-wheeled vehicles, which includes: An ambient temperature acquisition unit is used to acquire the real-time ambient temperature of the managed area. The power grid data acquisition unit is used to acquire the real-time load rate of the power grid in the managed area; The battery status acquisition unit is used to determine the remaining battery power and battery health in two-wheeled vehicles connected to a charging station. The main control unit is electrically connected to the ambient temperature acquisition unit, the power grid data acquisition unit, and the battery status acquisition unit, respectively. It is used to receive real-time ambient temperature, real-time power grid load rate, remaining power, and battery health. It determines the temperature compensation coefficient based on the real-time ambient temperature, the power grid load compensation coefficient based on the real-time power grid load rate, and the correction coefficient based on the remaining power and battery health. Finally, it determines the target charging power based on the preset charging base power, temperature compensation coefficient, power grid load compensation coefficient, and correction coefficient.

[0017] In this embodiment, by integrating four parameters—ambient temperature, real-time grid load rate, remaining charge, and battery health—for coordinated regulation, the charging power can be dynamically adjusted based on the real-time grid load rate, significantly reducing the impact on the grid during centralized fast charging at public charging stations and improving grid operational stability. Simultaneously, it can be specifically adapted to battery status and environmental conditions, reducing damage to batteries with high remaining charge and low health during fast charging and extending battery life. Furthermore, by determining the target charging power through the coordinated calculation of three coefficients and a preset base charging power, a multi-objective balance between fast charging efficiency, grid safety, and battery protection is effectively achieved, adapting to the application needs of promoting fast charging for electric two-wheeled vehicles and the centralized deployment of charging stations.

[0018] The aforementioned ambient temperature acquisition unit can employ an automotive-grade high-precision NTC temperature sensor, installed in a well-ventilated area of ​​the charging station (avoiding direct sunlight and rain), or it can be installed on the electric vehicle to specifically collect real-time ambient temperature data within the managed area. After collection, abnormal fluctuations can be removed using filtering algorithms to improve the stability and accuracy of the temperature data, and the processed temperature data is transmitted to the main control unit in real time.

[0019] The aforementioned power grid data acquisition unit can connect to the power grid dispatching platform of the management area through wired or wireless communication modules, or integrate a local power grid load detection module to collect the real-time load rate of the power grid (value range 0% to 100%).

[0020] The aforementioned battery status acquisition unit can establish a communication connection with the battery management system (BMS) of the electric two-wheeler through the charging interface to collect the battery's remaining charge (SOC, ranging from 0% to 100%) and battery health (SOH, ranging from 0% to 100%) in real time. The collected battery status data can be verified, invalid data can be removed to reflect the battery's current state of charge and health level as accurately as possible, and the data can be fed back to the main control unit in real time.

[0021] The aforementioned main control unit can employ a high-performance MCU processor, which is electrically connected to the ambient temperature acquisition unit, the power grid data acquisition unit, and the battery status acquisition unit via a bus or serial port on the charging interface, respectively, to receive the three types of parameter data in real time. Alternatively, the ambient temperature acquisition unit, the power grid data acquisition unit, and the battery status acquisition unit can transmit the data to the battery management system, which then communicates with the battery management system to obtain the data.

[0022] The main control unit can determine the positively correlated temperature compensation coefficient based on the real-time ambient temperature, the negatively correlated grid load compensation coefficient based on the real-time grid load rate, and the correction coefficient based on the remaining power (negatively correlated) and battery health (positively correlated). Then, it calculates the target charging power through the multiplication operation of "charging base power × temperature compensation coefficient × grid load compensation coefficient × correction coefficient" and sends real-time control commands to the power output module of the charging pile.

[0023] The aforementioned management area can be understood as the range of power supplied by the transformer in the area where the charging pile connected to the electric vehicle is located.

[0024] like Figure 1 As shown, this application embodiment also provides a smart fast charging method for electric two-wheeled vehicles. The smart fast charging method for electric two-wheeled vehicles is applied to the main control unit of the above-mentioned smart fast charging system for electric two-wheeled vehicles. The smart fast charging method for electric two-wheeled vehicles includes steps S100 to S600. Step S100: Obtain real-time ambient temperature, real-time grid load rate, remaining power, and battery health. Step S200: Determine the temperature compensation coefficient based on the real-time ambient temperature. The real-time ambient temperature is positively correlated with the temperature compensation coefficient. Step S300: Determine the grid load compensation coefficient based on the real-time grid load rate. The real-time grid load rate and the grid load compensation coefficient are negatively correlated. Step S400: Determine the correction coefficient based on the remaining power and battery health. The remaining power is negatively correlated with the correction coefficient, and the battery health is positively correlated with the correction coefficient. Step S500: Determine the target charging power based on the preset charging base power, temperature compensation coefficient, grid load compensation coefficient, and correction coefficient. Step S600: Adjust the real-time charging power of the charging pile to the electric two-wheeler according to the target charging power.

[0025] The method in this embodiment is based on the aforementioned intelligent fast charging system for electric two-wheelers, and therefore possesses all the beneficial effects brought by the aforementioned intelligent fast charging system for electric two-wheelers. Simultaneously, this method achieves multi-dimensional coordinated control through a closed-loop process of "four-parameter acquisition - three-coefficient determination - target power calculation - hourly power adjustment," breaking the limitations of single-parameter control. It effectively reduces the impact of centralized fast charging on the power grid by dynamically adapting to the grid state through real-time grid load rate, ensuring grid stability. Furthermore, it precisely adapts to battery operating conditions through ambient temperature, remaining charge, and battery health, reducing fast charging damage to batteries with high remaining charge and low health, and extending battery life. At the same time, under multi-objective constraints, it maximizes the preservation of the core advantages of fast charging, achieving a dynamic balance between fast charging efficiency, grid safety, and battery protection, adapting to the application needs of promoting fast charging for electric two-wheelers and the centralized deployment of public charging piles.

[0026] The aforementioned main control unit can receive data from various acquisition units through a preset communication link. For example, it can receive real-time ambient temperature data collected by the ambient temperature acquisition unit, real-time grid load rate data collected by the grid data acquisition unit, and remaining battery power and battery health data of the two-wheeled vehicle connected to the charging pile by the battery status acquisition unit.

[0027] The aforementioned main control unit can dynamically generate a temperature compensation coefficient based on real-time ambient temperature. For example, using 10℃ as a baseline suitable temperature (which can vary depending on the region to better achieve automatic power adjustment), the coefficient is calculated through a linear formula or a preset mapping relationship. The coefficient increases synchronously as the temperature rises and decreases synchronously as the temperature falls. This dynamic adaptation of temperature and charging power can reduce the problems of thermal runaway at high temperatures and lithium deposition at low temperatures. Furthermore, the positive correlation logic also aligns with the battery temperature characteristics, ensuring fast charging efficiency at suitable temperatures to a certain extent while strengthening battery protection at extreme temperatures, thus improving the environmental adaptability of the method.

[0028] The aforementioned main control unit can generate a grid load compensation coefficient based on the real-time grid load rate. For example, the lower the grid load rate, the closer the grid load compensation coefficient is to the upper limit, allowing for increased charging power; conversely, the higher the load rate, the closer the grid load compensation coefficient is to the lower limit, requiring charging power to be limited to adapt to dynamic fluctuations in grid load. This achieves real-time linkage between charging power and grid status, effectively reducing the risk of grid overload during peak periods of concentrated fast charging, while fully utilizing off-peak grid resources to improve charging resource utilization. Furthermore, the negative correlation logic accurately matches the grid's carrying capacity characteristics, balancing grid stability and charging efficiency, and is suitable for scenarios with centralized deployment of public charging piles.

[0029] The aforementioned main control unit can generate a correction coefficient by combining the remaining battery power and battery health. For example, the higher the remaining battery power, the greater the weighting and the lower the coefficient; conversely, the lower the battery health, the greater the weighting and the lower the coefficient. This achieves precise matching between charging power and the battery's own state, reducing the damage caused by overcharging batteries with high remaining power or fast charging batteries with low health, thus extending battery life. Furthermore, the dual-parameter collaborative correction logic covers the entire battery lifecycle, reducing charging safety hazards and improving the method's battery adaptability.

[0030] The aforementioned main control unit can calculate the target charging power according to the multiplication logic of "charging base power × temperature compensation coefficient × grid load compensation coefficient × correction coefficient". The calculation process responds to parameter changes in real time and dynamically updates the target power, which not only avoids the one-sidedness caused by single coefficient control, but also amplifies the synergistic effect of constraints in various dimensions through multiplication logic.

[0031] The aforementioned main control unit can convert the calculated target charging power into precise control commands and send them to the power output module of the charging pile. The power output module dynamically adjusts the output current and voltage according to the commands to achieve smooth switching of real-time charging power, while continuously feeding back the actual output power to the main control unit, forming a closed-loop control.

[0032] In some implementations, reference Figure 2 The above step S500 includes steps S510 to S520; Step S510: Perform a multiplication operation on the charging base power, temperature compensation coefficient, and grid load compensation coefficient to obtain the comprehensive base power; Step S520: Perform a multiplication operation on the comprehensive base power and the correction coefficient to obtain the target charging power.

[0033] The aforementioned main control unit can perform target charging power calculation according to the "layered multiplication operation" logic: First, it calls the preset charging base power and performs synchronous multiplication operation with the temperature compensation coefficient generated in step S200 and the grid load compensation coefficient generated in step S300 to obtain the comprehensive base power. During the calculation process, the coefficient values ​​are verified in real time to ensure that there are no abnormal values ​​that exceed the constraint range. Second, the calculated comprehensive base power is multiplied twice with the correction coefficient generated in step S400 to finally obtain the target charging power. At the same time, the intermediate calculation data is retained to facilitate subsequent fault diagnosis and parameter optimization.

[0034] In this implementation, a hierarchical calculation logic of "integrating external factors first and then correcting internal states" is adopted, making power regulation more hierarchical and precise. At the same time, step-by-step calculation facilitates flexible adjustment of the coefficient weight of individual links, adapting to the needs of different regional power grid characteristics and battery types. Moreover, the calculation logic is simple and efficient, reducing the computing power consumption of the main control unit, ensuring the real-time performance of power adjustment during fast charging, and further enhancing the multi-objective balance of fast charging efficiency, power grid stability, and battery protection.

[0035] In some implementations, if the target charging power exceeds the base charging power, the base charging power is assigned to the target charging power.

[0036] In this embodiment, by setting an upper limit constraint on the basic charging power, the problem of excessively high target charging power caused by high temperature compensation coefficients and grid load compensation coefficients (such as suitable ambient temperature and low grid load) can be effectively prevented. This prevents irreversible damage (such as cell bulging, capacity decay, and thermal runaway risk) to the high-rate lithium batteries of electric two-wheelers caused by over-power fast charging, while protecting hardware such as the charging pile power output module and preventing equipment failures caused by long-term operation above the rated power. This constraint mechanism, without weakening the core advantages of multi-parameter coordinated control, adds a safety threshold to the fast charging process, ensuring that the charging power is always within a reasonable range of "adapting to fast charging needs + hardware capacity limit + battery safety tolerance," further improving the reliability and safety of the method and adapting to the needs of centralized fast charging and high-frequency use scenarios at public charging piles.

[0037] In some implementations, reference Figure 3 Before adjusting the real-time charging power of the charging pile to the electric two-wheeler according to the target charging power, steps S700 and S800 are also included. Step S700: Obtain the cell temperature; In step S800, if the cell temperature exceeds a preset high temperature threshold, and / or if the battery health is below a preset low health threshold, an alarm strategy is executed.

[0038] This implementation accurately captures the real-time heating status of the battery cell, overcoming the limitation that ambient temperature cannot reflect the internal heating of the battery. It effectively prevents safety hazards caused by "low ambient temperature but localized overheating of the battery cell." Simultaneously, through dual threshold-triggered alarms, it provides timely warnings when the battery cell overheats, preventing thermal runaway risks, and also reminds users to pay attention to the low health status of the battery, avoiding irreversible damage caused by forced fast charging. It avoids blindly interrupting fast charging and affecting user experience, while responding quickly at the initial stage of risk, further improving the system's safety and reliability. It adapts to the needs of centralized fast charging at public charging stations and high-frequency use by multiple users, strengthening the safety protection of the battery and device during fast charging.

[0039] The alarm strategies mentioned above can be forced power reduction, notification alarm, a combination of multiple methods, or tiered alarm operations, which will not be elaborated here.

[0040] In some implementations, the temperature compensation coefficient is constrained by the following formula: K t = a + b × (T - T1); In the formula, K t is the temperature compensation coefficient, T is the real-time ambient temperature, T1 is the preset target temperature of the region, and a and b are both preset ambient temperature undetermined coefficients, with a being greater than b.

[0041] The aforementioned main control unit has the linear constraint formula built in. When using it, the core parameters are preset according to the climate characteristics of the application area. Among them, T1 (the preset target temperature of the area) is determined according to the local ambient temperature suitable for charging (e.g., it can be set to 10℃ in the central region to match its climate characteristics of no extreme cold, cold and humid winters and hot and humid summers). a and b are preset ambient temperature undetermined coefficients, which must satisfy a>b and preferably make the formula calculation result fall within the coefficient constraint range of 0.3 to 1.0 (e.g., set a=0.6, b=0.02).

[0042] During the calculation, the main control unit calls the filtered real-time ambient temperature T obtained in step S100, substitutes it into the formula for linear calculation, and takes 0.3 if the calculation result is lower than 0.3 and 1.0 if it is higher than 1.0. Finally, the constrained temperature compensation coefficient is output to the subsequent power calculation step.

[0043] It should be noted that the parameters can be flexibly adjusted through the charging pile backend to adapt to the needs of different regional climates or battery types. In practical application projects, parameters suitable for the target area can be obtained through simulation and field testing.

[0044] In this embodiment, the temperature compensation coefficient is constrained by a linear formula, enabling continuous and smooth adjustment of the coefficient with ambient temperature. This avoids abrupt changes in the coefficient caused by traditional interval-based control, improving the stability of power adjustment. T1 is set according to regional adaptation, and a and b can be flexibly adjusted, allowing the formula to adapt to different climate regions and enhancing the system's versatility. Furthermore, the formula logic is simple, the main control unit has high computational efficiency, and it can quickly respond to temperature changes, ensuring that the temperature compensation coefficient accurately matches the battery temperature characteristics. This improves the accuracy of subsequent target charging power control. Moreover, by setting an appropriate range for the temperature compensation coefficient, a reasonable coefficient can still be output stably even under extreme temperatures, effectively preventing battery damage caused by temperature mismatch. At the same time, it achieves multi-dimensional collaborative optimization in conjunction with grid load and battery state parameters.

[0045] In some implementations, the grid load compensation factor is constrained by the following formula: K m = c - d×β; In the formula, K m β is the power grid load compensation coefficient, β is the real-time power grid load rate, and c and d are both preset load undetermined coefficients, with c being greater than d.

[0046] The aforementioned main control unit has the linear constraint formula built in. When using it, the core parameters are preset according to the grid carrying capacity characteristics of the application scenario. Among them, c and d are preset load undetermined coefficients, which must meet the condition that c > d. It is preferred that the calculation result of the formula falls within the grid load compensation coefficient constraint range of 0.3 to 1.2 (for example, to adapt to the centralized layout scenario of public charging piles, c = 1.3 and d = 1.0, which not only meets the requirement of c > d, but also covers the entire range of grid load rate β = 0 to 1); β is the real-time grid load rate (value range 0 to 1) obtained and normalized in step S100.

[0047] During calculation, the main control unit calls the cached real-time grid load rate β, substitutes it into the formula for linear calculation, and obtains the calculation result. If the calculation result exceeds the range of 0.3 to 1.2, the corresponding boundary value can be automatically taken as the final coefficient. Parameters c and d can be remotely adjusted through the charging pile operation and maintenance backend to adapt to the load fluctuation patterns of different regional power grids (such as urban core areas and rural areas).

[0048] In this embodiment, the grid load compensation coefficient is constrained by a linear formula, enabling the coefficient to change continuously and smoothly with the grid load rate, thereby improving the stability of the charging process and the grid adaptability. Parameters c and d can be flexibly customized, allowing the formula to adapt to the carrying capacity of different grids (such as urban grids with large load fluctuations and rural grids with stable loads), enhancing the system's versatility. The formula logic is simple, the main control unit has high computational efficiency, and it can respond in real time to the dynamic fluctuations of grid load (such as when fast charging demand is concentrated during morning and evening peak hours), ensuring rapid coefficient adaptation. The negative correlation operation logic accurately matches the grid characteristics, maximizing the release of charging power during grid load troughs (ensuring fast charging efficiency) and actively limiting power during load peaks (avoiding grid overload). In scenarios with centralized deployment of public charging piles, this effectively balances the utilization rate of charging resources and the stability of grid operation, reducing the impact risk of centralized fast charging on the grid.

[0049] In some implementations, the correction factor is constrained by the following formula: K = e - f×S + g×H; In the formula, K is the correction coefficient, S is the remaining power, H is the battery health, and e, f, and g are preset auxiliary undetermined coefficients, with e being greater than f and g being greater than g.

[0050] The aforementioned main control unit incorporates this linear constraint formula. When using it, the core parameters are first preset according to the battery characteristics of the fast charging scenario for electric two-wheelers. Among them, e, f, and g are preset auxiliary undetermined coefficients, which must strictly satisfy the condition e > f > g. Preferably, the calculation result of the formula falls within the correction coefficient constraint range of 0.6 to 0.9 (for example, to adapt to mainstream electric two-wheeler batteries, set e = 0.9, f = 0.3, and g = 0.1, which not only conforms to the parameter size relationship but also covers the full range of values ​​for the remaining power S and the battery health H). S is the remaining power obtained and verified in step S100 (normalized to 0 to 1), and H is the battery health obtained simultaneously (normalized to 0 to 1).

[0051] During the calculation, the main control unit calls the cached S and H values ​​and substitutes them into the formula for linear operation: if the calculation result is lower than 0.6, it will automatically take 0.6; if it is higher than 0.9, it will take 0.9. Finally, the constrained correction coefficient will be output to the subsequent target charging power calculation step.

[0052] It should be noted that the e, f, and g parameters can be remotely adjusted through the charging pile operation and maintenance backend to adapt to the characteristics and requirements of batteries for different brands and types of electric two-wheelers.

[0053] In this embodiment, a linear formula constraint of "negative correlation cancellation of remaining power + positive correlation superposition of battery health" is used to achieve continuous and smooth adaptation of the correction coefficient to the dual core states of the battery (charged and healthy), thereby improving the stability of the fast charging process. The formula simultaneously takes into account overcharge protection of remaining power and protection of low battery health. The logic of dual-parameter collaborative correction is more in line with the actual working conditions of the battery, solving the problem that it is difficult to balance "overcharge protection when fully charged" and "damage prevention for old batteries" with single-parameter correction. The parameters e, f, and g can be flexibly customized, allowing the formula to adapt to the tolerance characteristics of different types of batteries and enhancing the versatility of the system. The formula calculation logic is simple, the main control unit consumes low computing power, and it can respond to changes in battery status in real time, ensuring that the correction coefficient accurately matches the current state of the battery, thereby improving the control accuracy of the target charging power. In risky scenarios such as high remaining power or low battery health, reasonable coefficient correction prevents the battery from being overloaded for fast charging, effectively extending battery life and reducing safety hazards while ensuring fast charging efficiency.

[0054] The intelligent fast charging method for electric two-wheeled vehicles provided in this application can be executed by an intelligent fast charging device for electric two-wheeled vehicles. This application uses an intelligent fast charging device for electric two-wheeled vehicles to execute the intelligent fast charging method as an example to illustrate the intelligent fast charging device for electric two-wheeled vehicles provided in this application.

[0055] This application also provides an intelligent fast charging device for electric two-wheeled vehicles, applied to the aforementioned intelligent fast charging system for electric two-wheeled vehicles. The intelligent fast charging device for electric two-wheeled vehicles includes: The parameter acquisition module is used to acquire real-time ambient temperature, real-time grid load rate, remaining power, and battery health. The first coefficient determination module is used to determine the temperature compensation coefficient based on the real-time ambient temperature. The real-time ambient temperature is positively correlated with the temperature compensation coefficient. The second coefficient determination module is used to determine the grid load compensation coefficient based on the real-time grid load rate. The real-time grid load rate is negatively correlated with the grid load compensation coefficient. The third coefficient determination module is used to determine the correction coefficient based on the remaining power and battery health. The remaining power is negatively correlated with the correction coefficient, while the battery health is positively correlated with the correction coefficient. The target power determination module is used to determine the target charging power based on the preset charging base power, temperature compensation coefficient, grid load compensation coefficient, and correction coefficient. The charging control module is used to adjust the real-time charging power of the charging pile to the electric two-wheeler according to the target charging power.

[0056] This application also provides an electronic device, including: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the above-described intelligent fast charging method for electric two-wheeled vehicles. The source table provided in this application can implement the various processes implemented in the above-described intelligent fast charging method embodiments for electric two-wheeled vehicles and achieve the same beneficial effects. To avoid repetition, it will not be described again here.

[0057] This application also provides a computer-readable storage medium storing computer-executable instructions that are executed by a processor or control module, causing the processor to perform the intelligent fast charging method for electric two-wheeled vehicles described above, for example, the method described above.

[0058] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0059] The functional blocks shown in the above structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. The programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM, floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0060] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0061] It should also be noted that the user information involved in this application, including but not limited to user device information and user personal information, and the data, including but not limited to data used for analysis, stored data, and displayed data, are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with relevant regulations. The acquisition, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations.

[0062] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus, and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0063] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. An intelligent fast charging system for electric two-wheeled vehicles, characterized in that, include: An ambient temperature acquisition unit is used to acquire the real-time ambient temperature of the managed area. The power grid data acquisition unit is used to acquire the real-time load rate of the power grid in the managed area; The battery status acquisition unit is used to determine the remaining battery power and battery health in two-wheeled vehicles connected to a charging station. The main control unit is electrically connected to the ambient temperature acquisition unit, the power grid data acquisition unit, and the battery status acquisition unit, respectively. It is used to receive real-time ambient temperature, real-time power grid load rate, remaining power, and battery health. It determines the temperature compensation coefficient based on the real-time ambient temperature, the power grid load compensation coefficient based on the real-time power grid load rate, and the correction coefficient based on the remaining power and battery health. Finally, it determines the target charging power based on the preset charging base power, temperature compensation coefficient, power grid load compensation coefficient, and correction coefficient.

2. A smart fast charging method for electric two-wheeled vehicles, characterized in that, Applied to the system of claim 1, the method includes the following steps: Obtain real-time ambient temperature, real-time grid load rate, remaining power, and battery health; The temperature compensation coefficient is determined based on the real-time ambient temperature, and the real-time ambient temperature is positively correlated with the temperature compensation coefficient. The power grid load compensation coefficient is determined based on the real-time power grid load rate, and the real-time power grid load rate is negatively correlated with the power grid load compensation coefficient. The correction coefficient is determined based on the remaining power and battery health. The remaining power is negatively correlated with the correction coefficient, while the battery health is positively correlated with the correction coefficient. The target charging power is determined based on the preset base charging power, temperature compensation coefficient, grid load compensation coefficient, and correction coefficient. Adjust the real-time charging power of the charging pile to the electric two-wheeler according to the target charging power.

3. The intelligent fast charging method for electric two-wheeled vehicles according to claim 2, characterized in that, Based on the preset base charging power, temperature compensation coefficient, grid load compensation coefficient, and correction coefficient, the target charging power is determined, including: The comprehensive base power is obtained by multiplying the charging base power, temperature compensation coefficient, and grid load compensation coefficient. The target charging power is obtained by multiplying the overall base power and the correction factor.

4. The intelligent fast charging method for electric two-wheeled vehicles according to claim 2, characterized in that, If the target charging power exceeds the base charging power, the base charging power will be assigned to the target charging power.

5. The intelligent fast charging method for electric two-wheeled vehicles according to claim 2, characterized in that, Before adjusting the real-time charging power of the charging station to the electric two-wheeler according to the target charging power, it also includes: Obtain the cell temperature; An alarm strategy is executed when the cell temperature exceeds a preset high temperature threshold, and / or when the battery health level falls below a preset low health threshold.

6. The intelligent fast charging method for electric two-wheeled vehicles according to claim 2, characterized in that, The temperature compensation coefficient is constrained by the following formula: K t = a +b×(T - T1); In the formula, K t is the temperature compensation coefficient, T is the real-time ambient temperature, T1 is the preset target temperature of the region, and a and b are both preset ambient temperature undetermined coefficients, with a being greater than b.

7. The intelligent fast charging method for electric two-wheeled vehicles according to claim 2, characterized in that, The power grid load compensation factor is constrained by the following formula: K m = c - d×β; In the formula, K m β is the power grid load compensation coefficient, β is the real-time power grid load rate, and c and d are both preset load undetermined coefficients, with c being greater than d.

8. The intelligent fast charging method for electric two-wheeled vehicles according to claim 2, characterized in that, The correction factor is constrained by the following formula: K = e - f×S + g×H; In the formula, K is the correction coefficient, S is the remaining power, H is the battery health, and e, f, and g are preset auxiliary undetermined coefficients, with e being greater than f and g being greater than g.

9. A smart fast charging device for electric two-wheeled vehicles, characterized in that, The electric two-wheeler intelligent fast charging device, applied to the intelligent fast charging system for electric two-wheelers as described in claim 1, comprises: The parameter acquisition module is used to acquire real-time ambient temperature, real-time grid load rate, remaining power, and battery health. The first coefficient determination module is used to determine the temperature compensation coefficient based on the real-time ambient temperature. The real-time ambient temperature is positively correlated with the temperature compensation coefficient. The second coefficient determination module is used to determine the grid load compensation coefficient based on the real-time grid load rate. The real-time grid load rate is negatively correlated with the grid load compensation coefficient. The third coefficient determination module is used to determine the correction coefficient based on the remaining power and battery health. The remaining power is negatively correlated with the correction coefficient, while the battery health is positively correlated with the correction coefficient. The target power determination module is used to determine the target charging power based on the preset charging base power, temperature compensation coefficient, grid load compensation coefficient, and correction coefficient. The charging control module is used to adjust the real-time charging power of the charging pile to the electric two-wheeler according to the target charging power.

10. An electronic device, characterized in that, Electronic devices include processors and memory storing computer program instructions; When the processor executes the computer program, it implements the intelligent fast charging method for electric two-wheeled vehicles as described in any one of claims 2 to 8.

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