An electric vehicle charging power control method, system and storage medium

Abstract

This application discloses a method, system, and storage medium for controlling the charging power of an electric vehicle. The method includes: acquiring the target charging completion time and target charging amount set by the user, as well as the current battery charge; calculating the remaining charge required and the remaining available charging time, wherein the remaining available charging time deducts the reserved buffer time, the derating time in the high charge range, and the safety margin time based on the battery state; determining the target average charging power for the next cycle based on the ratio of the remaining charge required to the remaining available charging time; and comparing the actual charge with the expected charge after the time cycle of each charging process. If there is a deviation, the target power for the next cycle is dynamically corrected bidirectionally based on the magnitude of the deviation and the urgency of the remaining time, ensuring that the corrected power does not exceed the safety limits of the battery and the charging pile. This application achieves precise matching between the charging process and the user's time needs, improving charging efficiency and user experience.

Description

Technical Field

[0001] This application relates to the field of power battery management systems and charging control, specifically to a method, system, and storage medium for controlling the charging power of an electric vehicle. Background Technology

[0002] Currently, mainstream DC fast charging systems generally adopt a control strategy aimed at "minimizing charging time." This means that within the battery's safety limits, charging is performed at a fixed maximum power until the battery reaches its state of charge (SOC) stage, after which the power is gradually reduced according to a preset derating curve. This leads to the following problems: (1) The timing and behavior do not match. The vehicle is often fully charged before the user’s expected departure time (e.g., parking for 2 hours and fully charging in 40 minutes), which leads to the subsequent long-term occupation of the charging space and the generation of additional space fees.

[0003] (2) Static control defects: The existing system lacks full-process, time-driven power planning. Even with delayed start function, it cannot correct the power trajectory in real time according to factors such as power fluctuation of charging pile and changes in battery health SOH to ensure punctuality. Summary of the Invention

[0004] This application provides a method, system, and storage medium for controlling the charging power of an electric vehicle, which can solve the technical problem in the prior art where the mismatch between time and behavior causes the vehicle to be fully charged before the user's expected departure time, resulting in the vehicle occupying the charging space for a long time and incurring additional occupancy fees.

[0005] In a first aspect, embodiments of this application provide a method for controlling the charging power of an electric vehicle, comprising: Within the current time period, obtain the current moment and the current battery charge level, as well as the user-defined target charging completion time and target charge amount; The remaining amount of charge to be added is calculated based on the target charging amount and the current charge level of the battery; the remaining available charging time is calculated based on the target charging completion time and the current time. Based on the remaining charge required and the remaining available charging time, the target average charging power for the next time period is determined, and the target charging power curve for the next time period is generated based on the target average charging power.

[0006] Preferably, the remaining available charging time is calculated based on the target charging completion time and the current time, specifically including the following steps: Get the preset buffer time; Calculate the difference between the target charging completion time and the current time, and subtract the preset buffer time from the difference to obtain the remaining available charging time; The preset buffer time includes a reserved end buffer time, a constant voltage derating charging time required for the high-charge charging range, and a safety margin time set based on the real-time battery temperature or health status.

[0007] Preferred options also include: After charging is completed in the current time period, obtain the actual amount of battery charge and the expected amount of charge to be added according to the target charging power curve of the current time period. Compare the actual amount of charge the battery has received with the expected amount of charge it should receive; If the actual charge received by the battery is greater than or less than the expected charge received, it indicates that the charging progress is abnormal in the current time period.

[0008] Preferably, if an abnormal charging progress occurs in the current time period, the following steps are performed: When the actual charge of the battery exceeds the expected charge, the target average charging power for the next time period is reduced by the real-time power correction amount to obtain the corrected target average charging power for the next time period. When the actual charge of the battery is less than the expected charge, the target average charging power for the next time period is increased by the real-time power correction amount to obtain the corrected target average charging power for the next time period.

[0009] Preferably, calculating the real-time power correction amount specifically includes the following steps: Obtain the deviation between the actual charge level and the expected charge level of the battery; The weighting coefficients representing the urgency of the time are determined based on the current remaining available charging time; The real-time power correction is calculated based on the deviation and weighting coefficient.

[0010] Preferably, after obtaining the corrected target average charging power for the next time period, the method further includes the following steps: The target average charging power for the next time period is compared with the maximum charging power allowed by the current battery and the maximum output power that the charging station can provide. If the target average charging power of the next time period after correction is greater than at least one of the maximum charging power allowed by the current battery and the maximum output power that the charging pile can provide, then the target average charging power of the next time period after correction will be limited to a preset range to obtain the final target average charging power of the next time period.

[0011] Preferably, the time required to complete charging is re-estimated based on the target average charging power for the next time period; If the re-estimated time required to complete charging is later than the user's target charging completion time, an early warning will be sent to the user that charging cannot be completed on time. At the same time, the re-estimated time required to complete charging will be sent as a time token to the charging station's operation backend, and the charging station's operation backend will be controlled to delay the start time of billing for the occupancy fee based on the time token.

[0012] Secondly, embodiments of this application provide an electric vehicle charging power control system, which includes: The user interaction and input module is used to collect the target charging completion time and target charging amount set by the user. The status acquisition module is used to obtain the current time and the current battery charge level within the current time period; The power planning module is used to calculate the remaining amount of charge to be added based on the target charging amount and the current amount of charge already added to the battery; calculate the remaining available charging time based on the target charging completion time and the current time; and determine the target average charging power for the next time period based on the remaining amount of charge to be added and the remaining available charging time. The control module is used to generate the target charging power curve for the next time period based on the target average charging power.

[0013] Preferably, the status acquisition module is also used to obtain the maximum allowable charging power of the current battery and the maximum output power that the charging pile can provide; The power planning module is also used to obtain the actual amount of battery charge after the current time period is completed, and the expected amount of charge to be charged according to the target charging power curve of the current time period; compare the actual amount of battery charge and the expected amount of charge; when the actual amount of battery charge is greater than or less than the expected amount of charge, it indicates that the charging progress of the current time period is abnormal. The control module is also used to calculate the real-time power correction amount and make adjustments based on the real-time power correction amount when the charging progress is abnormal in the current time period, so as to obtain the corrected target average charging power for the next time period; and to limit the corrected target average charging power for the next time period based on the maximum charging power allowed by the current battery and the maximum output power that the charging pile can provide, so as to output the final target average charging power for the next time period.

[0014] Thirdly, embodiments of this application provide a computer-readable storage medium storing an electric vehicle charging power control program, wherein when the electric vehicle charging power control program is executed by a processor, it implements the steps of an electric vehicle charging power control method.

[0015] The beneficial effects of the technical solutions provided in this application include: A time- and energy-driven dual-drive charging control method has been established. Firstly, in terms of precise response to user needs, traditional charging strategies passively adapt to a vehicle-to-charger model. This solution allows users to actively set departure time and target charge level, shifting charging services from standardized supply to personalized customization, significantly improving user experience and control. Secondly, this solution achieves time-domain optimized allocation of charging resources. By setting the target average charging power as a function of the remaining chargeable charge and remaining available charging time, the system can appropriately reduce power when time is ample to minimize battery heat load and aging, and increase power when time is tight to ensure timely completion. This achieves a balance between charging intensity, battery life, and grid load in the time dimension, representing a flexible control strategy with global optimization potential.

[0016] From a technical perspective, this solution is essentially a rolling time-domain optimization controller. It discretizes the entire charging process into continuous time periods. At the beginning of each period, based on the latest current time, the current battery charge level, and the user-set target, it recalculates an average power setpoint within a finite time domain. This model predictive control approach gives the system robustness against future uncertainties. Even if the initial estimation contains errors, it can be continuously corrected in subsequent periods to ensure the achievement of the final time target. This provides a reliable theoretical framework for achieving precise endpoint control in dynamic environments, thus solving the technical problem of time-behavior mismatch leading to vehicles often fully charging before the user's expected departure time, and resulting in prolonged occupancy of charging spaces and additional occupancy fees. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the general flow of the electric vehicle charging power control method of this application; Figure 2 This is a detailed flowchart illustrating the electric vehicle charging power control method of this application. Detailed Implementation

[0018] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0019] First, some of the technical terms used in this application will be explained to help those skilled in the art understand this application.

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0021] In a first aspect, embodiments of this application provide a method for controlling the charging power of an electric vehicle, comprising: Step 100: Within the current time period, obtain the current moment, the current battery charge level, and the user-set target charging completion time. and target charging amount; Step 200: Calculate the remaining charge required based on the target charge amount and the current charge amount already added to the battery. ;Calculate the remaining available charging time based on the target charging completion time and the current time; Step 300: Based on the remaining amount of electricity to be charged and the remaining available charging time, determine the target average charging power for the next time period. The target average charging power curve for the next time period is generated based on this target. The remaining amount of electricity to be charged is calculated from the user-defined target state of charge, the current state of charge, and the battery's currently available energy. ,in, The current state of charge, The target state of charge is denoted as Energy; Energy is the battery's current available energy. The battery's current available energy is affected by battery lifespan degradation. ,in The rated capacity of the battery is given; SOH represents the battery health status; the remaining usable charging time is... (Time margin); ,Should It will serve as a real-time benchmark for the target charging power curve and will be updated at fixed intervals.

[0022] Among them, the target average charging power for the next time period is determined. And based on the target average charging power, generate the target charging power curve for the next time period. This can be understood as: The target charging power curve is a piecewise function, including a ramp-up section and a power holding section. The power change rate in the ramp-up section does not exceed a preset threshold. The power setting of the power holding section is the same as... The corresponding feasible power value is In the next time period The time average value meets the preset power limit. Under the premise of battery / charging station power constraints, it should be equal to or as close as possible to Correction is performed by adjusting the duration or final power of the piecewise function to make the time average consistent with... Consistent.

[0023] Target charging power curve This is a piecewise function with two or more segments. The specific number of segments, the duration of each segment, and the power settings are adaptively determined based on the battery's allowable charging capacity, the charging pile's output capacity, and the power change rate constraint. The main formulas are as follows: In the (k)th control cycle, let the next time cycle be... The target average charging power for the next time period is determined based on the remaining energy required for charging and the remaining available charging time, and the target charging power curve for the next time period is generated accordingly. .

[0024] When the remaining available charging time is The target average charging power is:

[0025] Considering the preset power limit and the maximum allowable power of the battery Maximum allowable power of charging piles Define the upper limit of feasible power for this period:

[0026] The feasible target power for the power holding section is:

[0027] Let the actual charging power at the current moment be... The preset upper limit of power change rate is The duration of the uphill section is:

[0028] Target charging power curve This is a piecewise function, including an uphill section and a power-holding section (which can be further refined depending on the specific situation): Uphill section:

[0029] Power holding section:

[0030] In the next time period, the time-averaged power of the target power curve is defined as: From the above two forms, we can obtain: Under the premise of meeting the power limit and battery / charging station constraints, Equal to or as close as possible .

[0031] When there is no upper limit constraint and there is an adjustment margin, the power holding section can be corrected to make the average power consistent with... Consistent. The power of the power holding section can be changed from... Revised to : Change the power holding section to .

[0032] The above considerations are based on two segments. If the number of segments is to be increased, it is necessary to consider... Divide into N sub-segments, each with a duration of . The corresponding power is ,So :

[0033] And satisfy the average power constraint:

[0034] Simultaneously satisfying both power upper limit and rate of change constraints:

[0035] Where N, as well as It can be adaptively determined based on the battery's allowable charging capacity, the charging pile's output capacity, and the power change rate constraint.

[0036] The above steps establish a time- and energy-driven dual-drive charging control method. Firstly, regarding precise response to user needs, traditional charging strategies passively adapt to a vehicle-to-charger model. This solution allows users to actively set departure time and target charge level, shifting charging services from standardized supply to personalized customization, significantly improving user experience and control. Secondly, this solution achieves time-domain optimized allocation of charging resources. By setting the target average charging power as a function of the remaining chargeable charge and remaining available charging time, the system can appropriately reduce power when time is ample to minimize battery heat load and aging, and increase power when time is tight to ensure timely completion. This achieves a balance between charging intensity, battery life, and grid load in the time dimension, representing a flexible control strategy with global optimization potential.

[0037] From a technical perspective, this solution is essentially a rolling time-domain optimization controller. It discretizes the entire charging process into continuous time periods. At the beginning of each period, based on the latest current time, the current battery charge level, and the user-set target, it recalculates an average power setpoint within a finite time domain. This model predictive control approach gives the system robustness against future uncertainties. Even if the initial estimation contains errors, it can be continuously corrected in subsequent periods to ensure the achievement of the final time target. This provides a reliable theoretical framework for achieving precise endpoint control in dynamic environments, thus solving the technical problem of time-behavior mismatch leading to vehicles often fully charging before the user's expected departure time, and resulting in prolonged occupancy of charging spaces and additional occupancy fees.

[0038] In some preferred embodiments, the remaining available charging time is calculated based on the target charging completion time and the current time, specifically including the following steps: Get the preset buffer time; Calculate the difference between the target charging completion time and the current time, and subtract the preset buffer time from the difference to obtain the remaining available charging time; The preset buffer time includes a reserved end buffer time, a constant voltage derating charging time required for the high-charge charging range, and a safety margin time set based on the real-time battery temperature or health status.

[0039] in, ; Reserved end buffer time; This is the slow charging time that must be reserved for the high SOC range (derating range) due to safety restrictions; This provides an additional safety margin based on dynamic calculations of battery temperature and SOH.

[0040] By applying multiple safety and process corrections to the remaining available charging time, a more effective remaining available charging time that better reflects engineering realities is obtained. This is key to achieving high-reliability and high-precision time control; that is, by pre-subtracting the constant-voltage derating charging time necessary for the high-charge range. The system, during its initial planning, reserved ample time for the slow charging phase determined by the battery's chemical characteristics. This prevents the system from forcibly maintaining high power later to catch up with the charging schedule, effectively avoiding safety risks such as overcharging and lithium plating. The safety margin time is dynamically calculated based on real-time battery temperature or state of health (SOH). This allows the system to sense battery fatigue or discomfort and automatically allocate more recovery time, essentially integrating battery health management into time resource allocation for preventative protection. In principle, it transforms engineering experience, battery electrochemical models, and real-time status monitoring data into "conservative quantities" or "redundancy" in time planning. By introducing multiple time correction terms, it transforms the originally deterministic time calculation problem into a robust planning problem considering multiple constraints, ensuring that even in worst-case scenarios (such as poor battery condition or intermittent current limiting at the charging station), the system still has sufficient buffer time to complete the charging target, greatly enhancing the practicality and reliability of the entire control scheme.

[0041] In some preferred embodiments, it further includes: After charging is completed in the current time period, obtain the actual amount of battery charge and the expected amount of charge to be added according to the target charging power curve of the current time period. The actual battery charge level and expected charge amount Comparison; among which It is the amount of electricity that should theoretically be charged up to the current moment based on the target charging power curve; If the actual charge received by the battery is greater than or less than the expected charge received, it indicates that the charging progress is abnormal in the current time period.

[0042] This embodiment introduces a real-time progress monitoring and anomaly diagnosis mechanism for the charging process, which is a fundamental element for achieving closed-loop dynamic control. This endows the system with the ability to detect deviations, transforming the control process from open-loop execution of a preset curve to closed-loop tracking of the target trajectory. By monitoring the actual charge level of the battery after each charging cycle, the battery management system (BMS) provides feedback on the actual charge level received. The expected charging capacity is obtained by integrating the target power curve for this period. By comparing the data, the system can quantitatively evaluate the execution effect of the previous control cycle. This comparison not only determines whether the progress is ahead of schedule or behind schedule, but more importantly, it reveals the magnitude of the deviation, providing a data foundation for subsequent precise correction. The system detects various internal and external disturbances. Abnormal charging progress may stem from the charging pile's output power not reaching the commanded value (external power grid fluctuations), increased battery internal resistance leading to reduced actual received power (internal aging), or the BMS actively limiting current to protect the battery. This solution uses a unified energy deviation signal to characterize the combined impact of all these disturbances on the charging process, providing a concise and effective feedback information for the upper-level controller.

[0043] In some preferred embodiments, if an abnormal charging progress occurs in the current time period, the following steps are performed: When the actual charge of the battery exceeds the expected charge, the target average charging power for the next time period is reduced by the real-time power correction amount to obtain the corrected target average charging power for the next time period. When the actual charge of the battery is less than the expected charge, the target average charging power for the next time period is increased by the real-time power correction amount to obtain the corrected target average charging power for the next time period.

[0044] Right now: .

[0045] when (Lagging behind): The actual charging rate is lower than planned. To catch up with the time target, the system automatically fine-tunes and increases the target average charging power for the next cycle, and sends a power request. .

[0046] when (Ahead of Schedule): Actual charging rate exceeds plan, delaying energy injection to match. The system automatically reduces the target average charging power for the next cycle and sends a power request. .

[0047] The bidirectional correction capability is manifested in the precise locking of the charging completion time. When a lag in progress is detected (ΔE<0), the system catches up by increasing the target power for the next cycle; when an overshoot is detected (ΔE>0), it waits by reducing power. This bidirectional adjustment capability allows the energy injection curve of the charging process to be dynamically compressed or stretched, acting like an invisible hand to pull the charging completion time toward the user-set target time, effectively solving the pain point of premature or incomplete charging caused by various disturbances. Secondly, this solution achieves smooth optimization of the charging process. This solution is based on continuous fine-tuning of periodic deviations, making the adjustment of the power curve gradual and smooth, avoiding the impact of large power jumps on the battery, charging pile, and power grid, and improving system stability and equipment lifespan. From the perspective of control principles, this constitutes a complete negative feedback closed loop: deviation leads to correction, and correction reduces deviation.

[0048] In some preferred embodiments, calculating the real-time power correction specifically includes the following steps: Obtain the deviation between the actual charge level and the expected charge level of the battery; The weighting coefficients representing the urgency of the situation are determined based on the current remaining available charging time. The weighting coefficient increases as the remaining available charging time decreases; The real-time power correction is calculated based on the deviation and weighting coefficient, i.e. and .

[0049] This can be understood as: Remaining available charging time Construct a time probability distribution, calculate the time entropy, and then normalize it to obtain the weighting coefficients for the degree of time urgency. .

[0050] The time entropy weighted calculation of the weighting coefficients is explained below: Let the update period be Δt, and the current remaining available charging time be... The number of time slices is obtained by discretization:

[0051] No. The remaining time corresponding to each time slice:

[0052] Construction urgency and normalized to Implementing the probability distribution becomes increasingly urgent as the deadline approaches.

[0053] Where ε>0 is to prevent the denominator from being 0. Calculate time entropy and normalized to :

[0054] Obtain the weighting coefficients that characterize the urgency of time. :

[0055] The shorter the length, the more concentrated the distribution, and the lower the entropy. The larger the size, the more urgent the time commitment.

[0056] Reference power formula:

[0057] The ultimate target average charging power: .

[0058] The real-time power correction is obtained by subtracting the final target average charging power from the original target average charging power.

[0059] In this embodiment, based on the aforementioned basic correction logic, time urgency is introduced as a key weighting factor for adjusting the correction intensity, i.e., a time entropy weighting mechanism. When the remaining available time (ΔT_avail) is ample, even with some progress deviation, the system tends to adopt a smaller power correction. This maintains the stability of the charging process, avoids unnecessary power fluctuations, and gives the system more time to naturally adjust and absorb deviations, reflecting the optimization philosophy of trading time for stability. Conversely, when the remaining time is very tight (ΔT_avail is small), the weighting coefficient is the time entropy coefficient (…). ), As the power increases, the system will take more aggressive and larger-amplitude power corrections. At this point, ensuring timely completion becomes the highest priority control objective, and the system must take more decisive measures to quickly eliminate deviations, reflecting an emergency logic of trading intensity for time. This strategy of dynamically adjusting the gain with the remaining time allows the system to be calm and stable in the early stages of the charging process and agile and decisive in the later stages. From the perspective of control theory, this is equivalent to a proportional controller with time-varying gain. Its weighting coefficients are no longer fixed values, but rather functions of the remaining time ΔT_avail.

[0060] In some preferred embodiments, after obtaining the corrected target average charging power for the next time period, the method further includes the following steps: The target average charging power for the next time period is compared with the maximum charging power allowed by the current battery and the maximum output power that the charging station can provide. If the target average charging power for the next time period is corrected At least greater than the maximum charging power allowed by the current battery The maximum output power that the charging station can provide If at least one of the following is selected, the target average charging power for the next time period will be limited to a preset range to obtain the final target average charging power for the next time period.

[0061] In this embodiment, after calculating the time-optimized request power P_request, it must be compared with two key physical constraints: one is the maximum charging power that the battery can safely accept in its current state (such as temperature, voltage, and SOC). This is determined by the battery's chemical characteristics and the BMS's safety strategy; secondly, by the maximum output power that the charging station can stably provide under current conditions. This is limited by the charging pile's hardware capabilities, grid dispatch instructions, or load allocation within the station. By taking the smaller of these two limitations as the actual usable power limit, the system fundamentally eliminates serious safety issues such as battery thermal runaway, overcharging damage, or charging pile overload failures that may be caused by exceeding the requested power limit. Secondly, this scheme achieves graceful policy degradation under safety constraints. When the calculated requested power exceeds either safety limit, the system does not simply report an error and stop, but keeps the final executed power within a safe range. This means that when performance targets that must be completed on time conflict with safety boundaries, the system will prioritize safety and accept any potential delays in the time target.

[0062] In some preferred embodiments, it also includes The time required to complete charging is re-estimated based on the target average charging power for the next time period. If the re-estimated time required to complete charging is later than the user's target charging completion time, an early warning will be sent to the user that charging cannot be completed on time. At the same time, the re-estimated time required to complete charging will be sent as a time token to the charging station's operation backend, and the charging station's operation backend will be controlled to delay the start time of billing for the occupancy fee based on the time token.

[0063] The above achieves the synergy of rate reduction in high SOC ranges and current limiting at the pile end: If the maximum usable power is reduced due to increased SOC or excessively high battery temperature Less than The system will automatically stretch the power curve and recalculate the new one. And prompt the user (if) ).

[0064] If the charging pile has the maximum output power Below The system also stretches and corrects the curve. .

[0065] In this embodiment, a collaborative mechanism with the charging station's operation backend is introduced, enabling the linkage between technical control strategies and commercial service rules. First, after the system has undergone all possible optimizations and safety clamps, the estimated time required to complete charging is recalculated. Still later than the user-set time In such cases, the system proactively issues warnings to users. This gives users the right to know and the right to choose: they can choose to accept the delay or end charging early to arrange their subsequent trips. This transparent communication mechanism avoids users passively waiting without knowing the situation, significantly improving the friendliness and trustworthiness of the service.

[0066] Secondly, this solution addresses the issue of fairness in commercial billing caused by technical strategies. The system sends the re-estimated time required to complete charging as a time token to the charging station's backend. The backend system can then intelligently delay the start time of billing for the vehicle's parking space reservation fee based on this token. This means that as long as the vehicle strives to complete charging on time under the system's intelligent control, even if the user-set time is slightly delayed due to objective limitations (such as extremely poor battery condition or severely limited grid power), the user will not need to pay extra for this involuntary delay. This embodies the advanced concept of technology serving people and rules prioritizing user experience. The vehicle controller uploads the estimated result (time token) generated by its control logic to the cloud-based operating system, which adjusts its billing strategy accordingly and then applies the adjusted service rules (such as delayed billing) to the user.

[0067] The following provides a specific implementation step and a concrete example: S1. Input and Acquisition: Obtain user-defined settings. and ; Collect real-time status data of the battery and the pile end 13. S2. Initial Planning: Calculation 14; Calculate based on safety constraints and SOH ;based on Establish the initial target power curve.

[0068] S3. Enter control loop: with a fixed period Collect actual and .

[0069] S4. Deviation Calculation: The calculation theory should incorporate energy. and actual energy input The deviation was obtained. .

[0070] S5. Power Correction (Time Entropy Weighted): Based on... The sign and time entropy coefficient Execute bidirectional correction logic to generate the next cycle's... .

[0071] S6. Security Verification: [The following is a partial translation and requires context:] Constraints were verified against real-time battery temperature and high SOC derating curves.

[0072] S7. Command Issuance: Send the final command to the charging station. instruction.

[0073] S8. Termination Judgment: Continue looping S3-S7 until the condition is met. or (or Permissible security boundaries).

[0074] An electric vehicle equipped with an 80kWh battery requires approximately 48kWh of energy to charge from 30% to 90%. (User settings) minute.

[0075] Initial planning: System calculation The initial time is 85 minutes (with a 5-minute margin). It is approximately 33.8kW.

[0076] During operation: At the 30-minute mark, the power at the pile end dropped from 35kW to 25kW for 5 minutes due to grid fluctuations.

[0077] Corrective action: The system detected... (Charging progress is lagging). Due to... There are still 55 minutes left, time entropy coefficient At a moderate level. The system initiates a power-up strategy, which will... The power output was increased to 38kW, which is lower than the maximum available power of 50kW, in order to catch up with the schedule in a gentler way.

[0078] Result: The vehicle accurately reached 90% SOC within 90 minutes ± 2 minutes, avoiding premature charging and prolonged occupancy.

[0079] Secondly, an electric vehicle charging power control system is provided, comprising: The user interaction and input module is used to collect the target charging completion time and target charging amount set by the user. The status acquisition module is used to obtain the current time and the current battery charge level within the current time period; The power planning module is used to calculate the remaining amount of charge to be added based on the target charging amount and the current amount of charge already added to the battery; calculate the remaining available charging time based on the target charging completion time and the current time; and determine the target average charging power for the next time period based on the remaining amount of charge to be added and the remaining available charging time. The control module is used to generate the target charging power curve for the next time period based on the target average charging power.

[0080] In some preferred embodiments, the status acquisition module is also used to obtain the maximum charging power allowed by the current battery and the maximum output power that the charging pile can provide; The power planning module is also used to obtain the actual amount of battery charge after the current time period is completed, and the expected amount of charge to be charged according to the target charging power curve of the current time period; compare the actual amount of battery charge and the expected amount of charge; when the actual amount of battery charge is greater than or less than the expected amount of charge, it indicates that the charging progress of the current time period is abnormal. The control module is also used to calculate the real-time power correction amount and make adjustments based on the real-time power correction amount when the charging progress is abnormal in the current time period, so as to obtain the corrected target average charging power for the next time period; and to limit the corrected target average charging power for the next time period based on the maximum charging power allowed by the current battery and the maximum output power that the charging pile can provide, so as to output the final target average charging power for the next time period.

[0081] The functions of each module in the electric vehicle charging power control device correspond to the steps in the above-mentioned electric vehicle charging power control method embodiment, and their functions and implementation processes will not be described in detail here.

[0082] Thirdly, embodiments of this application provide an electric vehicle charging power control device, which can be a device with data processing capabilities such as a personal computer (PC), a laptop computer, or a server.

[0083] In this embodiment, the electric vehicle charging power control device may include a processor, a memory, a communication interface, and a communication bus.

[0084] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0085] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting devices within the electric vehicle charging power control equipment, as well as interfaces used for interconnecting the electric vehicle charging power control equipment with other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0086] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0087] The processor can be a general-purpose processor, which can call the electric vehicle charging power control program stored in the memory and execute the electric vehicle charging power control method provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the electric vehicle charging power control program is called can be referred to in the various embodiments of the electric vehicle charging power control method of this application, and will not be repeated here.

[0088] Fourthly, embodiments of this application also provide a computer-readable storage medium.

[0089] The present application provides a computer-readable storage medium storing an electric vehicle charging power control program, wherein when the electric vehicle charging power control program is executed by a processor, it implements the steps of the electric vehicle charging power control method described above.

[0090] The method implemented when the electric vehicle charging power control program is executed can be referred to in various embodiments of the electric vehicle charging power control method of this application, and will not be repeated here.

[0091] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0092] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0093] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0094] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0095] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0096] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0097] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for controlling the charging power of an electric vehicle, characterized in that, It includes: Within the current time period, obtain the current moment and the current battery charge level, as well as the user-defined target charging completion time and target charge amount; The remaining amount of charge to be added is calculated based on the target charging amount and the current charge level of the battery; the remaining available charging time is calculated based on the target charging completion time and the current time. Based on the remaining charge required and the remaining available charging time, the target average charging power for the next time period is determined, and a target charging power curve for the next time period is generated based on the target average charging power.

2. The electric vehicle charging power control method as described in claim 1, characterized in that, Based on the target charging completion time and the current time, the remaining available charging time is calculated, specifically including the following steps: Get the preset buffer time; Calculate the difference between the target charging completion time and the current time, and subtract the preset buffer time from the difference to obtain the remaining available charging time; The preset buffer time includes a reserved end buffer time, a constant voltage derating charging time required for the high-charge charging range, and a safety margin time set based on the real-time battery temperature or health status.

3. The electric vehicle charging power control method as described in claim 1, characterized in that, Also includes: After charging is completed in the current time period, obtain the actual amount of battery charge and the expected amount of charge to be added according to the target charging power curve of the current time period. Compare the actual amount of charge the battery has received with the expected amount of charge it should receive; If the actual charge received by the battery is greater than or less than the expected charge received, it indicates that the charging progress is abnormal in the current time period.

4. The electric vehicle charging power control method as described in claim 3, characterized in that, If an abnormal charging progress occurs in the current time period, perform the following steps: When the actual charge of the battery exceeds the expected charge, the target average charging power for the next time period is reduced by the real-time power correction amount to obtain the corrected target average charging power for the next time period. When the actual charge of the battery is less than the expected charge, the target average charging power for the next time period is increased by the real-time power correction amount to obtain the corrected target average charging power for the next time period.

5. The electric vehicle charging power control method as described in claim 4, characterized in that, The calculation of the real-time power correction amount specifically includes the following steps: Obtain the deviation between the actual charge level and the expected charge level of the battery; The weighting coefficients representing the urgency of the time are determined based on the current remaining available charging time; The real-time power correction is calculated based on the deviation and weighting coefficient.

6. The electric vehicle charging power control method as described in claim 5, characterized in that, The target average charging power for the next time period, after correction, also includes the following steps: The target average charging power for the next time period is compared with the maximum charging power allowed by the current battery and the maximum output power that the charging station can provide. If the target average charging power of the next time period after correction is greater than at least one of the maximum charging power allowed by the current battery and the maximum output power that the charging pile can provide, then the target average charging power of the next time period after correction will be limited to a preset range to obtain the final target average charging power of the next time period.

7. The electric vehicle charging power control method as described in claim 6, characterized in that, Also includes: The time required to complete charging is re-estimated based on the target average charging power for the next time period. If the re-estimated time required to complete charging is later than the user's target charging completion time, an early warning will be sent to the user that charging cannot be completed on time. At the same time, the re-estimated time required to complete charging will be sent as a time token to the charging station's operation backend, and the charging station's operation backend will be controlled to delay the start time of billing for the occupancy fee based on the time token.

8. An electric vehicle charging power control system, characterized in that, It includes: The user interaction and input module is used to collect the target charging completion time and target charging amount set by the user. The status acquisition module is used to obtain the current time and the current battery charge level within the current time period; The power planning module is used to calculate the remaining amount of charge to be added based on the target charging amount and the current charge of the battery; and to calculate the remaining available charging time based on the target charging completion time and the current time. Based on the remaining amount of electricity to be charged and the remaining available charging time, determine the target average charging power for the next time period; The control module is used to generate the target charging power curve for the next time period based on the target average charging power.

9. The electric vehicle charging power control system as described in claim 8, characterized in that: The status acquisition module is also used to obtain the maximum charging power allowed by the current battery and the maximum output power that the charging pile can provide. The power planning module is also used to obtain the actual amount of battery charge after the current time period is completed, and the expected amount of charge to be charged according to the target charging power curve of the current time period; compare the actual amount of battery charge and the expected amount of charge; when the actual amount of battery charge is greater than or less than the expected amount of charge, it indicates that the charging progress of the current time period is abnormal. The control module is also used to calculate the real-time power correction amount when the charging progress is abnormal in the current time period, and to make adjustments based on the real-time power correction amount to obtain the target average charging power for the next time period after correction. And to limit the target average charging power for the next time period based on the current maximum allowed charging power of the battery and the maximum output power that the charging pile can provide, so as to output the final target average charging power for the next time period.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores an electric vehicle charging power control program, wherein when the electric vehicle charging power control program is executed by a processor, it implements the steps of the electric vehicle charging power control method as described in any one of claims 1 to 7.

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