An electric vehicle charging power dynamic optimization method and system

Abstract

This invention discloses a method and system for dynamically optimizing the charging power of electric vehicles, relating to the field of electric vehicle charging technology. The method includes: real-time acquisition of battery SOC, temperature status data, and charging power output from the charging pile during the charging process; joint state evaluation based on the acquired battery status data to determine the current charging stage of the battery; matching a corresponding charging adjustment strategy according to the current charging stage, and generating a dynamic charging power control command based on the real-time battery status data to regulate the charging power output from the charging pile; and performing closed-loop dynamic charging power control optimization based on real-time feedback of battery status data until charging is complete. This invention can achieve a dual improvement in charging efficiency and safety, solving the problems of low efficiency and poor safety in existing charging strategies.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle charging technology, and in particular to a method and system for dynamic optimization of electric vehicle charging power. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the rapid development of the electric vehicle industry, fast charging technology has become crucial for improving the user experience. Currently, although a collaborative control mechanism has been established between the electric vehicle's Battery Management System (BMS) and charging stations, the charging strategies installed in charging stations are mostly based on the battery's State of Charge (SOC) monitored by the BMS, using static parameters (such as fixed current or power) for charging. This lack of dynamic adjustment of charging power leads to low charging efficiency and numerous safety hazards. For example, in low-temperature environments, the battery's internal resistance increases; directly using high-power charging will not only significantly reduce charging efficiency but also cause irreversible damage to the battery's internal structure. In high-temperature environments, the battery's heat generation rate accelerates; continuous high-power charging can easily trigger thermal runaway, leading to battery fires, explosions, and other safety accidents. During the high SOC stage, continuing high-power charging can easily cause overcharging, accelerating battery life degradation. Summary of the Invention

[0004] To address the shortcomings of the existing technologies, this invention provides a method and system for dynamic optimization of electric vehicle charging power. Through bidirectional communication between the charging pile and the electric vehicle's BMS, the system enables real-time acquisition and phased evaluation of battery status, and matches differentiated dynamic optimization and control strategies for charging power. Through closed-loop optimization, the system achieves a dual improvement in charging efficiency and safety, solving the problems of low efficiency and poor safety in existing charging strategies.

[0005] In a first aspect, the present invention provides a method for dynamically optimizing the charging power of electric vehicles.

[0006] A method for dynamically optimizing electric vehicle charging power, utilizing charging piles to charge electric vehicles, and involving bidirectional communication between the charging piles and the electric vehicle's BMS module, includes: Real-time acquisition of battery SOC, temperature status data, and charging power output from charging piles during the charging process of electric vehicles; A joint state assessment is performed based on the acquired battery state data to determine the current charging stage of the battery. Based on the current charging stage of the battery, a corresponding charging adjustment strategy is matched, and combined with real-time battery status data, a dynamic charging power control command is generated to control the charging power output of the charging pile. Based on real-time feedback of battery status data, the closed-loop charging power is dynamically adjusted and optimized until charging is complete.

[0007] A further technical solution is that the charging stage includes: a low-temperature pretreatment stage, a conventional fast charging stage, a high SOC trickle charging stage, and a high-temperature warning stage; A joint state assessment is performed based on the acquired battery state data to determine the current charging stage of the battery, including: When the battery temperature is lower than the first temperature threshold, the battery is determined to be in the low temperature pretreatment stage. When the battery temperature is higher than the first temperature threshold but lower than the second temperature threshold, and the battery SOC is lower than the first SOC threshold, the battery is determined to be in the normal fast charging stage. When the battery temperature is higher than the first temperature threshold and lower than the second temperature threshold, and the battery SOC is higher than the first SOC threshold, the battery is determined to be in the high SOC trickle stage. When the battery temperature exceeds the second temperature threshold, the battery is determined to be in a high-temperature warning stage.

[0008] A further technical solution involves triggering a charging preheating strategy during the low-temperature pretreatment stage to control the charging pile to output a constant low charging power for charging. During the regular fast charging phase, charging efficiency is dynamically adjusted based on real-time battery status data and preset rules. During the high SOC trickle charging phase, the charging pile is controlled to output a constant charging power for charging. During high-temperature warning periods, charging stations will be shut down.

[0009] A further technical solution involves dynamically adjusting charging efficiency based on real-time battery status data and preset rules during the regular fast charging phase, including: When the battery SOC is lower than the second SOC threshold, fast charging is performed at the maximum allowable power of the charging pile. When the battery SOC is between the first SOC threshold and the second SOC threshold, the charging power is adjusted by setting a gradient for the increase step size of the charging power, and a temperature compensation factor is introduced to optimize the adjusted charging power for fast charging.

[0010] A further technical solution is that the temperature compensation factor changes with the real-time temperature of the battery, and its calculation formula is as follows: ; Optimizing charging power based on a temperature compensation factor is expressed as: ; In the above formula, Indicates the temperature compensation factor. Indicates the real-time temperature of the battery. Indicates charging power. This indicates the charging power after optimization by the temperature compensation factor.

[0011] A further technical solution involves controlling the charging pile to output a constant charging power during the high SOC trickle charging phase. When the rate of increase of the battery's real-time temperature exceeds the set value, the charging pile output power is reduced until the rate of increase of the battery temperature drops to a safe value and remains so for a set duration. Then, the charging power is gradually increased in stages and slowly until charging is complete.

[0012] Secondly, the present invention provides a dynamic optimization system for electric vehicle charging power.

[0013] A dynamic optimization system for electric vehicle charging power, comprising: The BMS module communicates and interacts bidirectionally with the charging pile to obtain real-time data on battery SOC and temperature status of electric vehicles during the charging process. The charging pile is used to obtain the charging power output of the charging pile in real time, and to control the charging power output of the charging pile according to the received charging power dynamic adjustment command. The charging efficiency optimization module is used to perform joint state evaluation based on the acquired battery status data to determine the current charging stage of the battery; match the corresponding charging adjustment strategy according to the current charging stage of the battery, and generate dynamic charging power control instructions based on real-time battery status data; and perform closed-loop dynamic charging power control optimization based on real-time feedback battery status data until charging is complete.

[0014] Thirdly, the present invention also provides an electronic device, comprising: a memory for storing executable instructions; and a processor for implementing the above-described method for dynamic optimization of electric vehicle charging power when executing the executable instructions stored in the memory.

[0015] Fourthly, the present invention also provides a computer-readable storage medium storing executable instructions for causing a processor to execute the executable instructions to implement the above-described method for dynamic optimization of electric vehicle charging power.

[0016] Fifthly, the present invention also provides a computer program product comprising executable instructions stored in a computer-readable storage medium; wherein, when the processor of an electronic device reads the executable instructions from the computer-readable storage medium and executes the executable instructions, the above-mentioned method for dynamic optimization of electric vehicle charging power is implemented.

[0017] The above one or more technical solutions have the following beneficial effects: This invention provides a method and system for dynamic optimization of electric vehicle charging power. Through bidirectional communication between the charging pile and the electric vehicle's BMS, it achieves real-time acquisition and phased evaluation of battery status, and matches differentiated dynamic optimization and control strategies for charging power. Closed-loop optimization achieves a dual improvement in charging efficiency and safety, solving the problems of low efficiency and poor safety in existing charging strategies. This invention performs joint state evaluation based on real-time monitoring of battery SOC and temperature, dividing the charging process into four stages: low-temperature pretreatment, regular fast charging, high SOC trickle charging, and high-temperature warning. Targeted safety control strategies are matched for each risk scenario, avoiding various charging safety hazards from the source. For example, in the low-temperature pretreatment stage, constant low-power preheating avoids lithium deposition, dendrite growth, and internal short circuits caused by low-temperature high-power charging. When the monitored battery temperature exceeds a preset safety threshold, charging is immediately terminated, fundamentally preventing serious safety accidents such as battery fires and explosions.

[0018] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0020] Figure 1 This is a flowchart of the electric vehicle charging power dynamic optimization method in Embodiment 1 of the present invention. Detailed Implementation

[0021] It should be noted that the following detailed descriptions are exemplary and are intended only to describe specific embodiments and to provide further explanation of the invention, and are not intended to limit the scope of exemplary embodiments of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0022] Example 1 As noted in the background section, the existing coordination mechanisms between charging piles and electric vehicle BMS hardware have significant shortcomings. Some charging piles still use a fixed current / power for charging during the constant current phase, without considering the impact of battery SOC (State of Charge) and temperature on lithium-ion migration rates. This leads to increased battery internal resistance and decreased charging efficiency at low temperatures. Furthermore, during fast charging, the migration rate of lithium ions between the positive and negative electrodes needs to match the current input. When the charging rate exceeds 2C, the risk of lithium deposition increases significantly, potentially causing dendrite growth and internal short circuits, affecting charging safety. In addition, existing BMS thermal management strategies mostly rely on passive heat dissipation, which cannot respond to battery heat generation characteristics in real time, leading to accelerated battery life degradation at high temperatures.

[0023] To address the issues of low efficiency and poor safety in existing charging strategies, this embodiment proposes a dynamic optimization method for electric vehicle charging power. This method utilizes charging piles to charge electric vehicles, and the charging piles and the electric vehicle's BMS module engage in bidirectional communication. The specific steps include: Step S1: Real-time acquisition of battery SOC, temperature status data, and charging power output by the charging pile during the charging process of the electric vehicle; Step S2: Perform a joint state assessment based on the acquired battery state data to determine the current charging stage of the battery; Step S3: Match the corresponding charging adjustment strategy according to the current charging stage of the battery, and generate a dynamic charging power control command based on real-time battery status data to control the charging power output of the charging pile. Step S4: Based on the real-time feedback of battery status data, perform closed-loop dynamic adjustment and optimization of charging power until charging is complete.

[0024] The following content will provide a more detailed description of the electric vehicle charging power dynamic optimization method proposed in this embodiment.

[0025] like Figure 1 As shown, in step S1, the battery status data and the charging power data output by the charging pile are acquired in real time during the charging process of the electric vehicle.

[0026] Specifically, when using charging piles to charge electric vehicles, a two-way communication connection is pre-established between the charging pile and the electric vehicle's BMS module. The BMS module uses high-precision sensors to collect core status data such as battery SOC and temperature in real time during the charging process of the electric vehicle. The sampling frequency is not less than 1kHz, and the data acquisition error is ≤±0.1%.

[0027] In this embodiment, the BMS hardware adopts a distributed architecture, which can improve the reliability and scalability of the system. Each cell is equipped with an independent monitoring chip, such as the TI BQ76PL455A. This monitoring chip has high-precision measurement capabilities and can accurately acquire parameters such as voltage, current, and temperature of the cell in real time, providing accurate data support for the BMS's battery state estimation and protection control. In addition, the distributed architecture can also reduce the risk of single-point failure. When a monitoring chip fails, it will not affect the monitoring of other cells, thereby improving the stability of the entire BMS system and avoiding control errors caused by data errors.

[0028] The charging pile integrates a CAN bus communication module, establishing a bidirectional data channel with the BMS. It collects its own output charging power data in real time, and simultaneously receives battery status data transmitted by the BMS module through the bidirectional communication channel. The data transmission delay is <50ms, enabling the synchronous acquisition of battery SOC, temperature and charging pile output power data. This meets the real-time data requirements of dynamic charging control and ensures that the charging pile can quickly respond to changes in battery status.

[0029] In this embodiment, the charging pile main control board, as the core control unit of the entire system, is equipped with an ARM Cortex-M7 processor. This processor features high performance and low power consumption, with a main frequency of up to several hundred MHz, enabling it to quickly process large amounts of data and complex algorithm calculations. The charging pile integrates a CAN bus communication module. The CAN bus has high reliability and real-time performance, ensuring the stability and timeliness of data transmission between the charging pile and the BMS, with a transmission delay of less than 50ms, meeting the real-time requirements of dynamic charging control. In addition, the charging pile is also equipped with a 4G communication module, which enables data interaction between the charging pile and the remote monitoring center, facilitating remote management and maintenance of the charging pile, such as remotely updating algorithm parameters and obtaining the operating status of the charging pile.

[0030] As one implementation method, this embodiment uses the CAN 2.0B standard as the communication protocol between the charging pile and the BMS. The CAN 2.0B standard has high reliability and real-time performance, which can meet the data transmission requirements of dynamic charging control. Its data frame format adopts a standard frame format, including an arbitration field, control field, data field, CRC field, ACK field, and frame end field. The arbitration field is used to determine the data priority, the control field is used to identify the type and length of the data frame, the data field is used to carry the actual data information, the CRC field is used for data verification, the ACK field is used for the receiver's acknowledgment, and the frame end field is used to indicate the end of the data frame.

[0031] Furthermore, to achieve ordered communication between the charging pile and the BMS, the data frame ID is pre-assigned as follows: 0x1806F4B4: BMS → Charging Pile (Battery Status Data). The BMS sends battery status information such as SOC, temperature, and SOH to the charging pile through the data frame with this ID, so that the charging pile can adjust the charging strategy according to the battery status. 0x1807F4B4: Charging pile → BMS (control command). The charging pile sends control commands to the BMS through the data frame with this ID, such as start charging, stop charging, adjust charging power, etc. The BMS executes the corresponding operation according to the received control command.

[0032] Preferably, to ensure the accuracy of data transmission, after establishing the communication link between the charging pile and the BMS, the communication transmission process is verified before subsequent data transmission. Specifically, during the verification process, a CRC-16 checksum is appended to each data frame. CRC-16 is a commonly used data verification method that generates a checksum by performing specific calculations on the data frame. After receiving the data frame, the receiver also performs the calculation and compares the result with the received checksum. If they match, the data transmission is correct; otherwise, if they do not match, an error has occurred during transmission and the data needs to be retransmitted. By using CRC-16 checksum verification, the bit error rate can be controlled to less than [a certain value]. This level effectively improves the reliability of data transmission.

[0033] In step S2, a joint state assessment is performed based on the acquired battery state data to determine and classify the current charging stage of the battery.

[0034] Specifically, the charging pile performs a joint state assessment based on the acquired battery SOC and temperature status data. According to preset threshold standards, the battery charging process is divided into four charging stages: low temperature pretreatment stage, regular fast charging stage, high SOC trickle charging stage, and high temperature warning stage. The specific judgment rules are as follows: (1) Low temperature pretreatment stage: When the battery temperature is lower than the first temperature threshold (5℃), the battery is determined to be in this stage. At this time, the battery internal resistance is large and it is not suitable for high-power charging. Preheating treatment is required first. (2) Regular fast charging stage: When the battery temperature is higher than the first temperature threshold (5℃) and lower than the second temperature threshold (45℃), and the battery SOC is lower than the first SOC threshold (80%), the battery is determined to be in this stage. At this time, the battery is suitable for high-power charging, which is the core stage for improving charging efficiency. (3) High SOC trickle charging stage: When the battery temperature is higher than the first temperature threshold (5℃) and lower than the second temperature threshold (45℃), and the battery SOC is higher than the first SOC threshold (80%), the battery is determined to be in this stage. At this time, the battery is close to full charge. Continuing to charge at high power will easily cause overcharging. Low power trickle charging is required. (4) High temperature warning stage: When the battery temperature is higher than the second temperature threshold (45°C), the battery is determined to be in this stage. At this time, the battery is at risk of thermal runaway and charging must be terminated immediately to ensure safety.

[0035] In this embodiment, the preferred first temperature threshold is 5°C, the preferred second temperature threshold is 45°C, and the preferred first state of charge (SOC) threshold is 80%, while the preferred second SOC threshold is set to 30%, serving as the dividing point for power gradient adjustment during the conventional fast charging phase. Preferably, in practical applications, the threshold parameters can be flexibly adjusted according to the actual scenario, such as battery model and charging pile power.

[0036] By using the above method, a joint assessment based on temperature and SOC is conducted to accurately identify charging risk scenarios such as excessive internal resistance at low temperatures, thermal runaway at high temperatures, and overcharging at high SOC, and classify them into corresponding processing stages. That is, the charging process is divided into four stages: low temperature pretreatment, regular fast charging, high SOC trickle charging, and high temperature warning. This avoids the single mode of traditional static charging strategies and enables fine-grained identification of the battery's state throughout the entire charging process, making subsequent power regulation more targeted.

[0037] In step S3, based on the battery charging stage determined in the previous step, a corresponding charging adjustment strategy is matched, and combined with real-time battery status data, a dynamic charging power control command is generated to control the charging power output of the charging pile.

[0038] Specifically, the battery charging stages are divided based on real-time battery joint state assessment, and corresponding charging regulation strategies are matched for each stage. Combined with real-time collected battery SOC and temperature state data, dynamic charging power control commands are generated to precisely regulate the output charging power of the charging pile. The specific control strategies for each stage are as follows: (1) Low temperature pretreatment stage: preheating low power charging.

[0039] During the low-temperature pretreatment stage, a preheating strategy is triggered to control the charging pile to output a constant low charging power for charging. In this embodiment, the preferred charging power is 1.5kW. Preheating of the battery is achieved through low-power charging, avoiding lithium deposition and dendrite growth problems caused by direct high-power charging in low-temperature environments, preventing internal short circuits in the battery, ensuring charging safety, and avoiding a sudden drop in charging efficiency caused by excessive internal resistance of the battery. At the same time, the BMS module monitors the battery temperature changes in real time and feeds them back to the charging pile to ensure that the battery temperature rises steadily during low-power charging, avoiding damage to the internal structure of the battery due to sudden temperature changes, maintaining the stability of battery performance, and monitoring the battery temperature until the battery temperature reaches the first temperature threshold (5°C), completing this stage and automatically switching to the regular fast charging stage.

[0040] (2) Regular fast charging stage: dynamic gradient power + temperature compensation charging.

[0041] During the regular fast charging phase, the charging power is dynamically adjusted based on real-time battery SOC and temperature status data, combined with preset rules, to achieve efficient fast charging. This is specifically divided into two sub-steps: First, full-power fast charging: When the battery SOC is lower than the second SOC threshold (30%), the charging pile is controlled to fast charge at the maximum allowable power, making full use of the charging characteristics of the battery in the low SOC stage, rapidly increasing the battery capacity within the battery's safe tolerance range, significantly shortening the charging time in the low capacity stage, and improving the overall charging efficiency. Second, a combination of gradient adjustment and temperature compensation for fast charging: When the battery SOC is between the second SOC threshold (30%) and the first SOC threshold (80%), the charging power is gradient-adjusted by setting a charging power increase step size (this step size is the charging power increase value per unit SOC, such as 5kW / 10% SOC). This allows the charging current to precisely match the migration rate of lithium ions at the positive and negative electrodes, avoiding lithium deposition caused by excessive power, while also considering charging efficiency and solving the problem of mismatch between traditional fixed power and battery state. At the same time, a temperature compensation factor is introduced to optimize the gradient-adjusted charging power, using the optimized power for fast charging. By introducing this temperature compensation factor, the charging power can be adaptively adjusted according to the real-time battery temperature, effectively offsetting the charging efficiency loss caused by the increase in battery internal resistance in low-temperature environments, maximizing charging efficiency while ensuring charging safety.

[0042] The temperature compensation factor dynamically changes with the real-time temperature of the battery to offset the charging efficiency loss caused by the increased internal resistance of the battery in low-temperature environments. Its calculation formula is as follows: ; In the above formula, For temperature compensation factor, This is the real-time battery temperature (unit: °C), with 25 °C being the optimal charging temperature for the battery.

[0043] Furthermore, the current charging power is optimized based on the temperature compensation factor, calculated using the following formula: ; In the above formula, The charging power is adjusted by the gradient of the charging power growth step size. This is the charging power optimized by the temperature compensation factor.

[0044] By combining SOC gradient and temperature compensation, the charging power can be adapted to the real-time state changes of the battery in the 30%-80% range, avoiding the limitations of single parameter control and achieving a balance between efficiency and safety in this core fast charging stage.

[0045] (3) High SOC trickle stage: constant trickle charging + abnormal power regulation.

[0046] During the high SOC trickle charging phase, the charging pile is first controlled to output a constant power for trickle charging. In this embodiment, the preferred trickle charging power is 45kW to avoid overcharging of the battery caused by high-power charging during the high SOC phase, reduce the intensity of internal chemical reactions in the battery, and slow down the rate of battery life degradation. At the same time, the BMS module monitors the rate of increase of battery temperature in real time. If the rate of increase of battery temperature exceeds a set value (e.g., 0.5℃ / min), abnormal power regulation is immediately triggered, i.e.: First, the charging pile quickly reduces the output charging power within a preset time (5 seconds), preferably by 30kW, to reduce battery heat generation; Secondly, continuously monitor the rate of battery temperature rise until it drops to a safe value (0.1℃ / min) and continue for a set time (5min); Finally, the charging power is gradually increased in stages and slowly. It is first increased to 40kW while monitoring the battery status. Once no abnormalities are detected, it is then increased to 45kW until charging is complete. This staged, gradual power increase, with battery status monitored at each stage, avoids the impact of sudden power increases on the battery and minimizes the influence on the overall charging time, maximizing efficiency while ensuring safety.

[0047] (4) High temperature warning stage: Emergency termination of charging.

[0048] During the high-temperature warning phase, when the battery temperature exceeds a preset safety threshold, a charging termination command is immediately generated. This commands the charging station to stop outputting charging power, terminating the charging process and fundamentally preventing serious safety accidents such as battery fires and explosions caused by thermal runaway. A notification is also displayed on the vehicle's touchscreen. Preferably, the BMS module continuously monitors the battery temperature until it drops below the second temperature threshold (45°C). Only after the fault has been resolved can the charging process be restarted, preventing users from forcibly charging before the fault is resolved and improving the safety and controllability of the charging process.

[0049] Furthermore, corresponding charging adjustment strategies are implemented for the different charging stages mentioned above to achieve a more efficient and safer electric vehicle charging process. This will be further explained through the following description of the entire charging process. For example, in cold winters, when the ambient temperature drops to -10°C, the battery's SOC (State of Charge) is only 20%. The low battery temperature and remaining charge make direct high-power charging not only inefficient but also potentially damaging to the battery. Therefore, the charging optimization strategy proposed in this embodiment is adopted, and its execution process is as follows: First, temperature detection and request transmission. The BMS (Battery Management System) continuously monitors the battery temperature in real time. When the battery temperature is detected to be below 5°C, the BMS immediately sends a preheating request signal to the charging station through a specific communication protocol. This signal contains key information such as the current battery temperature and SOC, so that the charging station can accurately understand the battery status.

[0050] Then, the heating module starts and preheats, entering the low-temperature pretreatment stage. Upon receiving the preheating request, the charging pile quickly activates its pre-configured heating module, which uses high-efficiency heating elements and outputs a stable power of 1.5kW to begin preheating the battery. During preheating, the BMS continuously monitors changes in battery temperature and feeds the temperature data back to the charging pile in real time. The charging pile dynamically adjusts the heating power based on the feedback information (fine-tuning within allowable ranges to ensure a smooth heating process) to guarantee uniform heating of the battery.

[0051] Next, the system switches to fast charging mode and enters the regular fast charging phase. When the BMS detects that the battery temperature has risen to 5°C, it immediately sends a command to the charging station to switch to fast charging mode. Upon receiving the command, the charging station quickly shuts down the heating module and simultaneously switches the charging power to a fast charging mode of 60kW or higher. At this point, the battery has reached the temperature conditions suitable for high-power charging, enabling it to efficiently absorb electrical energy and quickly increase its SOC.

[0052] In the above process, the charging pile first performs fast charging at its maximum allowable power, making full use of the charging characteristics of the battery in the low SOC stage to quickly increase the battery capacity. During this process, the BMS monitors the battery SOC in real time. When the battery SOC is between the second SOC threshold (30%) and the first SOC threshold (80%), it begins to adjust the charging power in a gradient of 5kW / 10% SOC steps. At the same time, a temperature compensation factor is introduced to optimize the gradient-adjusted charging power, and fast charging is performed with the optimized power. By introducing a temperature compensation factor, it is ensured that the adaptively adjusted charging power can maximize charging efficiency while preventing the charging battery temperature from exceeding the safety threshold, thus ensuring charging safety.

[0053] Finally, as the charging process continues, the BMS monitors the battery's SOC in real time. When the SOC reaches 80%, considering that continuing to charge at high power in a high SOC state may adversely affect the battery's lifespan, the BMS automatically sends a power reduction request to the charging station. After receiving the request, the charging station enters the high SOC trickle phase, and within 5 seconds, the charging power is smoothly reduced from 60kW to 45kW to continue the remaining charging process at a lower power, ensuring battery charging safety and extending battery lifespan.

[0054] By employing the aforementioned low-temperature charging optimization strategy, the charging time is reduced by 22% compared to the traditional unoptimized charging method, significantly improving charging efficiency and reducing the waiting time for users in cold environments. Simultaneously, throughout the entire charging process, the battery temperature fluctuation remains within the set temperature fluctuation range, and the battery temperature does not exceed the safe temperature threshold, effectively avoiding damage to the battery's internal structure and performance caused by large temperature fluctuations, thus ensuring the battery's stability and safety.

[0055] As a further implementation, safety control is implemented during the high SOC trickle charging phase. Specifically, when the electric vehicle's battery SOC reaches 85% and the battery temperature is 40°C, the battery is in a state of high SOC and relatively high temperature. Under these conditions, if high-power charging continues, the internal chemical reactions of the battery will intensify, and the temperature rise rate may be too rapid, potentially leading to thermal runaway and seriously threatening battery safety and vehicle safety. Therefore, this embodiment implements a high SOC phase safety control strategy, the execution process of which is as follows: First, temperature rise rate monitoring and early warning. The BMS has a high-precision temperature monitoring function, which can measure the battery temperature in real time and accurately, and calculate the temperature rise rate. When the BMS detects that the battery temperature rise rate exceeds 0.5℃ / min, it immediately determines that the battery is in a potentially dangerous state and quickly sends an early warning signal to the charging station. This early warning signal contains detailed information such as battery temperature, temperature rise rate, and SOC, so that the charging station can fully understand the abnormal situation of the battery.

[0056] Then, the charging power is rapidly reduced. After receiving the warning signal from the BMS, the charging station's internal control system responds within 5 seconds, quickly reducing the charging power from the current 60kW to 30kW. This rapid power reduction effectively reduces the battery's charging current, thereby lowering the rate of chemical reactions within the battery, slowing the temperature rise, and preventing the risk of thermal runaway. During the power reduction process, the charging station monitors various battery parameters in real time to ensure a smooth operation without causing additional stress to the battery.

[0057] Next, the charging power is gradually restored to a higher level. Once the BMS detects that the rising battery temperature trend is under control and the temperature gradually stabilizes, if the rate of temperature increase drops below 0.1℃ / min and remains below this level for a period of time, the charging station begins to gradually restore the charging power. This power restoration process uses a phased, slow increase method. First, the power is increased from 30kW to 40kW. After monitoring the battery temperature and various parameter changes for a period of time (e.g., 5 minutes), if everything is normal (i.e., the safe charging requirements are met), the power is then increased to 45kW, and charging continues until the entire charging process is completed. This gradual power restoration method ensures that the battery continues to charge in a safe state while minimizing the impact on charging time.

[0058] By implementing a safety control strategy during the high SOC trickle phase, the risk of thermal runaway that may occur in batteries under high SOC and high temperature conditions can be avoided, ensuring the safety of the battery and the vehicle. At the same time, through actual testing and long-term tracking, research shows that this strategy reduces the battery life degradation rate by 30%, effectively extending the battery's lifespan, reducing user operating costs, and improving the overall reliability and economy of electric vehicles.

[0059] In step S4, based on the real-time feedback of battery status data, the above-mentioned control process continues to be executed to optimize the closed-loop charging power dynamic control until charging is complete.

[0060] Specifically, the BMS module feeds back battery SOC, temperature, and other status data to the charging pile in real time. Based on the real-time data, the charging pile repeats steps S2-S3 to continuously evaluate the battery charging stage, match the control strategy, and generate power control commands. If the battery status changes and crosses a stage, the charging pile immediately switches to the charging adjustment strategy for the corresponding stage. If the battery status fluctuates slightly within a certain stage, the charging pile performs fine-tuned power adjustments according to preset rules, achieving closed-loop dynamic control and optimization of charging efficiency until the battery SOC reaches 100%, completing the entire charging process.

[0061] This embodiment, through the above-described settings, uses the conventional fast charging phase as the core charging phase. In this phase, a refined power control strategy is designed, incorporating full-power fast charging, gradient power adjustment, and temperature compensation. During the low SOC phase, fast charging is performed at the maximum allowable power of the charging pile, fully utilizing the charging characteristics of the battery during low charge levels for rapid energy replenishment. When the SOC reaches a set range, the charging power is adjusted according to a set step size gradient to match the migration rates of the lithium-ion positive and negative electrodes. Simultaneously, a temperature compensation factor is used to adaptively optimize the power, effectively offsetting the charging efficiency loss caused by increased battery internal resistance in low-temperature environments. Compared to traditional charging methods, this embodiment can shorten charging time while improving charging efficiency, significantly reducing user charging waiting time and optimizing the user experience of the electric vehicle. Furthermore, the high SOC trickle charging phase employs constant low-power charging to prevent overcharging and battery damage. A temperature rise rate monitoring mechanism is also added, rapidly reducing the charging power when the temperature is abnormal to prevent the battery from aging rapidly due to prolonged exposure to high temperatures. Simultaneously, during the conventional fast charging phase, gradient power adjustment and temperature compensation ensure that the charging power always adapts to the real-time battery status, avoiding battery damage caused by a mismatch between power and battery status.

[0062] This embodiment reduces battery losses during charging and significantly lowers the rate of battery life degradation through refined power regulation and temperature control throughout the entire process.

[0063] Example 2 This embodiment provides a dynamic optimization system for electric vehicle charging power, specifically including: The BMS module communicates and interacts bidirectionally with the charging pile to obtain real-time data on battery SOC and temperature status of electric vehicles during the charging process. The charging pile is used to obtain the charging power output of the charging pile in real time, and to control the charging power output of the charging pile according to the received charging power dynamic adjustment command. The charging efficiency optimization module is used to perform joint state evaluation based on the acquired battery status data to determine the current charging stage of the battery; match the corresponding charging adjustment strategy according to the current charging stage of the battery, and generate dynamic charging power control instructions based on real-time battery status data; and perform closed-loop dynamic charging power control optimization based on real-time feedback battery status data until charging is complete.

[0064] In this embodiment, a joint state assessment is performed based on the acquired battery state data to determine the current charging stage of the battery, including the low-temperature pretreatment stage, the regular fast charging stage, the high SOC trickle charging stage, and the high-temperature warning stage. Then, a corresponding charging adjustment strategy is matched according to the charging stage, and a corresponding dynamic adjustment strategy for charging power is executed, specifically: When the battery temperature is lower than the first temperature threshold, the battery is determined to be in the low temperature pretreatment stage. In this stage, the charging preheating strategy is triggered to control the charging pile to output a constant small charging power for charging. When the battery temperature is higher than the first temperature threshold and lower than the second temperature threshold, and the battery SOC is lower than the first SOC threshold, the battery is determined to be in the normal fast charging stage. In this stage, the charging efficiency is dynamically adjusted according to the real-time battery status data and the preset rules. When the battery temperature is higher than the first temperature threshold and lower than the second temperature threshold, and the battery SOC is higher than the first SOC threshold, the battery is determined to be in the high SOC trickle stage. In this stage, the charging pile is controlled to output a constant charging power for charging. When the battery temperature exceeds the second temperature threshold, the battery is determined to be in a high-temperature warning stage, during which the charging station is controlled to terminate charging.

[0065] Furthermore, to achieve efficient fast charging, during the regular fast charging phase, charging efficiency is dynamically adjusted based on real-time battery status data and preset rules, including: When the battery SOC is lower than the second SOC threshold, fast charging is performed at the maximum allowable power of the charging pile. When the battery SOC is between the first SOC threshold and the second SOC threshold, the charging power is adjusted by setting a gradient for the increase step size of the charging power, and a temperature compensation factor is introduced to optimize the adjusted charging power for fast charging.

[0066] The temperature compensation factor varies with the real-time temperature of the battery, and its calculation formula is as follows: ; Furthermore, the charging power is optimized based on the temperature compensation factor, expressed as: ; In the above formula, Indicates the temperature compensation factor. Indicates the real-time temperature of the battery. Indicates charging power. This indicates the charging power after optimization by the temperature compensation factor.

[0067] As a further implementation method, in order to ensure the balance between charging efficiency and safety during the high SOC stage, during the high SOC trickle stage, the charging pile is first controlled to output a constant charging power for charging. When the rate of increase of the battery's real-time temperature is detected to exceed the set value, the charging pile output charging power is reduced until the rate of increase of the battery temperature is reduced to a safe value and continues for a set time. At this time, the charging power is gradually increased in stages and slowly until charging is completed.

[0068] Example 3 This embodiment provides an electronic device, including: a memory for storing executable instructions; and a processor for executing the executable instructions stored in the memory to implement the method provided in this embodiment.

[0069] Example 4 This embodiment also provides a computer-readable storage medium storing executable instructions, which, when executed by a processor, will cause the processor to execute the method described above in this embodiment.

[0070] Example 5 This embodiment provides a computer program product including executable instructions, which are computer instructions; the executable instructions are stored in a computer-readable storage medium. When the processor of an electronic device reads the executable instructions from the computer-readable storage medium and executes the executable instructions, the electronic device performs the method described in this embodiment.

[0071] The steps and methods involved in Embodiments 2 to 5 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0072] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0073] The above description is only a preferred embodiment of the present invention. Although the specific implementation of the present invention has been described in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that, based on the technical solution of the present invention, various modifications or variations that can be made by those skilled in the art without creative effort are still within the scope of protection of the present invention.

Claims

1. A method for dynamically optimizing electric vehicle charging power, characterized in that, Using charging piles to charge electric vehicles, with bidirectional communication between the charging piles and the electric vehicle's BMS module, including: Real-time acquisition of battery SOC, temperature status data, and charging power output from charging piles during the charging process of electric vehicles; A joint state assessment is performed based on the acquired battery state data to determine the current charging stage of the battery. Based on the current charging stage of the battery, a corresponding charging adjustment strategy is matched, and combined with real-time battery status data, a dynamic charging power control command is generated to control the charging power output of the charging pile. Based on real-time feedback of battery status data, the closed-loop charging power is dynamically adjusted and optimized until charging is complete.

2. The method of claim 1, wherein, The charging phase includes: low temperature pretreatment phase, conventional fast charging phase, high SOC trickle charging phase, and high temperature warning phase; A joint state assessment is performed based on the acquired battery state data to determine the current charging stage of the battery, including: When the battery temperature is lower than the first temperature threshold, the battery is determined to be in the low temperature pretreatment stage. When the battery temperature is higher than the first temperature threshold but lower than the second temperature threshold, and the battery SOC is lower than the first SOC threshold, the battery is determined to be in the normal fast charging stage. When the battery temperature is higher than the first temperature threshold and lower than the second temperature threshold, and the battery SOC is higher than the first SOC threshold, the battery is determined to be in the high SOC trickle stage. When the battery temperature exceeds the second temperature threshold, the battery is determined to be in a high-temperature warning stage.

3. The method of claim 2, wherein, During the low-temperature pretreatment stage, a charging preheating strategy is triggered to control the charging pile to output a constant low charging power for charging. During the regular fast charging phase, charging efficiency is dynamically adjusted based on real-time battery status data and preset rules. During the high SOC trickle charging phase, the charging pile is controlled to output a constant charging power for charging. During high-temperature warning periods, charging stations will be shut down.

4. The method of claim 3, wherein, During the regular fast charging phase, charging efficiency is dynamically adjusted based on real-time battery status data and preset rules, including: When the battery SOC is lower than the second SOC threshold, fast charging is performed at the maximum allowable power of the charging pile. When the battery SOC is between the first SOC threshold and the second SOC threshold, the charging power is adjusted by setting a gradient for the increase step size of the charging power, and a temperature compensation factor is introduced to optimize the adjusted charging power for fast charging.

5. The method of claim 4, wherein, The temperature compensation factor changes with the real-time temperature of the battery, and its calculation formula is as follows: ； Optimizing charging power based on a temperature compensation factor is expressed as: ； In the above formula, Indicates the temperature compensation factor. Indicates the real-time temperature of the battery. Indicates charging power. This indicates the charging power after optimization by the temperature compensation factor.

6. The method of claim 3, wherein, During the high SOC trickle charging phase, the charging pile is controlled to output a constant charging power for charging. When the rate of increase of the battery's real-time temperature exceeds the set value, the charging pile output power is reduced until the rate of increase of the battery temperature drops to a safe value and remains so for a set duration. Then, the charging power is gradually increased in stages and slowly until charging is complete.

7. An electric vehicle charging power dynamic optimization system, characterized in that, include: The BMS module communicates and interacts bidirectionally with the charging pile to obtain real-time data on battery SOC and temperature status of electric vehicles during the charging process. The charging pile is used to obtain the charging power output of the charging pile in real time, and to control the charging power output of the charging pile according to the received charging power dynamic adjustment command. The charging efficiency optimization module is used to perform joint state evaluation based on the acquired battery state data to determine the current charging stage of the battery; match the corresponding charging adjustment strategy according to the current charging stage of the battery, and generate dynamic charging power control instructions based on real-time battery state data. Based on real-time feedback of battery status data, the closed-loop charging power is dynamically adjusted and optimized until charging is complete.

8. An electronic device, comprising: include: Memory, used to store executable instructions; The processor, when executing executable instructions stored in the memory, implements the electric vehicle charging power dynamic optimization method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The device stores executable instructions that, when executed by a processor, implement the electric vehicle charging power dynamic optimization method according to any one of claims 1-6.

10. A computer program product, characterised in that, The computer program product includes executable instructions stored in a computer-readable storage medium; When the processor of the electronic device reads the executable instructions from the computer-readable storage medium and executes the executable instructions, the method for dynamic optimization of electric vehicle charging power according to any one of claims 1-6 is implemented.

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