Liquid-cooled supercharging charging control method and device, electronic equipment and storage medium

Abstract

The application provides a liquid-cooled super-charging charging control method and device, electronic equipment and storage medium, and belongs to the field of electric vehicle charging. The method comprises the following steps: obtaining a first target parameter of a liquid-cooled charging pile, wherein the first target parameter comprises a working parameter of the liquid-cooled charging pile and a power grid parameter of a power grid where the liquid-cooled charging pile is located; compensating the first target parameter based on the ambient temperature of the environment where the liquid-cooled charging pile is located to obtain a second target parameter; and controlling the liquid-cooled charging pile to be in different working modes according to different conditions met by the second target parameter, wherein the liquid-cooled parameters of the liquid-cooled charging pile are different when the liquid-cooled charging pile is in different working modes. The liquid-cooled super-charging charging control method and device, electronic equipment and storage medium provided by the application can significantly improve the efficiency and safety of high-power charging of electric vehicles.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of electric vehicle charging, and more particularly relates to a liquid-cooled super-charging control method and device, an electronic device, and a storage medium. BACKGROUND

[0002] With the rapid popularization of electric vehicles, the efficiency and safety of charging technology have become the core challenges in the industry. Traditional air-cooled charging piles are limited by heat dissipation efficiency and are difficult to meet the heat dissipation needs of high-power charging, resulting in a decrease in charging speed, a shortening of equipment life, and even the risk of heat runaway. Liquid cooling technology, with its high thermal conductivity and low noise, has become a key solution for super-charging systems, but existing liquid cooling solutions still have problems such as uneven cooling and dynamic response lag, which affect charging efficiency and battery health. Therefore, an intelligent liquid-cooled super-charging control method and device are urgently needed to achieve precise temperature control and charging optimization at high power. SUMMARY

[0003] The application aims to provide a liquid-cooled super-charging control method and device, an electronic device, and a storage medium.

[0004] The first aspect of the application embodiment provides a liquid-cooled super-charging control method, which comprises:

[0005] obtaining a first target parameter of a liquid-cooled charging pile, the first target parameter comprising a working parameter of the liquid-cooled charging pile and a power grid parameter of a power grid where the liquid-cooled charging pile is located;

[0006] compensating the first target parameter based on an ambient temperature of an environment where the liquid-cooled charging pile is located to obtain a second target parameter;

[0007] controlling the liquid-cooled charging pile to be in different working modes according to different conditions met by the second target parameter, wherein the liquid-cooled parameters of the liquid-cooled charging pile are different when the liquid-cooled charging pile is in different working modes.

[0008] The second aspect of the application embodiment provides a liquid-cooled super-charging control device, which comprises:

[0009] a data acquisition module configured to obtain a first target parameter of a liquid-cooled charging pile, the first target parameter comprising a working parameter of the liquid-cooled charging pile and a power grid parameter of a power grid where the liquid-cooled charging pile is located;

[0010] a data expansion module configured to compensate the first target parameter based on an ambient temperature of an environment where the liquid-cooled charging pile is located to obtain a second target parameter;

[0011] The power adjustment module is configured to control the liquid-cooled charging pile to be in different working modes according to different conditions of the second target parameter, wherein the liquid-cooled parameters of the liquid-cooled charging pile are different when the liquid-cooled charging pile is in different working modes.

[0012] In a third aspect, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the liquid-cooled super-charging control method described above are implemented.

[0013] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the steps of the liquid-cooled super-charging control method described above are implemented.

[0014] In a fifth aspect, a computer program product is provided, which includes a computer program or computer executable instructions. When the computer program or computer executable instructions are executed by a processor, the steps of the liquid-cooled super-charging control method described above are implemented.

[0015] The liquid-cooled super-charging control method and device, electronic device, and storage medium provided by the embodiments of the present application have the following beneficial effects. Through intelligent multi-mode control, predictive regulation, neural network optimization, and other technologies, the present application can reduce the impact on the charging system and electric vehicles caused by uneven heat dissipation and response lag of the liquid-cooled charging pile in a high-power charging scenario, and achieve a coordinated leap in charging efficiency, safety, and device reliability. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0017] Figure 1 A flowchart of the liquid-cooled super-charging control method provided by an embodiment of the present application is shown in the figure.

[0018] Figure 2 A structural block diagram of the liquid-cooled super-charging control device provided by an embodiment of the present application is shown in the figure.

[0019] Figure 3 A schematic block diagram of the electronic device provided by an embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0020] In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular architectures, technologies, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application can be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

[0021] In order to make the purpose, technical scheme and advantages of the present application clearer, the following will be described by specific embodiments in conjunction with the drawings.

[0022] Reference will be made to Figure 1 , Figure 1 The flowchart of the liquid-cooled super-charging charging control method provided by an embodiment of the present application can include the following steps.

[0023] S101: Obtain a first target parameter of a liquid-cooled charging pile, the first target parameter including an operating parameter of the liquid-cooled charging pile and a power grid parameter of a power grid where the liquid-cooled charging pile is located.

[0024] In the embodiment, the first target parameter can be a flow rate of the current cooling liquid of the liquid-cooled charging pile, a charging power mutation value, a voltage fluctuation value and an external temperature value, etc. The liquid-cooled charging pile can use a high-frequency sampling Hall current / voltage sensor to collect current or voltage signals in real time during the charging process, and calculate the power change rate through a differential algorithm, so as to realize dynamic monitoring and regulation of the charging power.

[0025] For example, if the charging power jumps from 200kW to 400kW in 0.1 seconds, the mutation value is 200kW / s.

[0026] In the embodiment, the voltage fluctuation monitoring can use a wide-band voltage sampling module to capture the instantaneous fluctuation of the power grid voltage, and combine with FFT analysis of harmonic components. The voltage sampling module can be, for example, AD7606, which is a high-performance, multi-channel, synchronous sampling ADC specially designed for high-precision data acquisition scenarios such as power monitoring. In the liquid-cooled super-charging charging control system, high-precision monitoring of voltage fluctuation can ensure the stability and safety of the charging process.

[0027] In the embodiment, temperature detection can deploy multiple-point temperature sensors outside the liquid-cooled charging pile heat dissipation air outlet and wave-cooling pipeline, and take the average value as the external temperature value.

[0028] S102: Compensate the first target parameter based on the ambient temperature of the environment where the liquid-cooled charging pile is located, to obtain a second target parameter.

[0029] In this embodiment, the liquid-cooled charging pile can work in an extreme environment temperature, such as a low temperature of-30℃ or a high temperature of 50℃. The heat dissipation efficiency will change significantly. For example, in a high-temperature environment, the cooling liquid heat dissipation capacity decreases, and the flow rate needs to be increased to avoid overheating. In a low-temperature environment, the viscosity of the cooling liquid increases, and the flow rate needs to be reduced or the pipeline needs to be preheated. The present application uses dynamic temperature compensation to optimize the performance of the liquid-cooled charging pile.

[0030] Specifically, the second target parameter generated after the ambient temperature compensation is not simply adding a new parameter, but dynamically modifying and expanding the first target parameter to make it more suitable for actual working conditions. For example, the first target parameter is input into a long short-term memory neural network to compensate for the first target parameter and add derived parameters, such as the maximum allowed power, cooling liquid flow rate, and voltage fluctuation threshold.

[0031] S103: controlling the liquid-cooled charging pile to be in different working modes according to different conditions met by the second target parameter, wherein the liquid-cooled parameters of the liquid-cooled charging pile are different when the liquid-cooled charging pile is in different working modes.

[0032] In this embodiment, the liquid-cooled charging pile has three working modes. The first working mode is a normal follow-up mode, and the liquid-cooled supercharging can control the liquid-cooled flow rate and flow speed according to the first number of influence factors affecting the liquid-cooled effect. The second working mode is a transition mode, and the liquid-cooled supercharging works at a fixed flow rate and flow speed in this stage. The third working mode is a super follow-up mode, and the liquid-cooled supercharging can control the liquid-cooled flow rate and flow speed according to the second number of influence factors affecting the liquid-cooled effect, and perform advance compensation, which can predict and compensate some, reduce the adjustment amount in the next cycle, and realize pre-adjustment. The first number is less than the second number.

[0033] When the first working mode is switched to the second working mode, the flow rate and flow speed in the second working mode are the flow rate and flow speed in the first working mode before the switch. When the third working mode is switched to the second working mode, the flow rate and flow speed in the second working mode are the flow rate and flow speed in the second working mode before the switch.

[0034] From the above, it can be concluded that the intelligent control system of the liquid-cooled charging pile proposed in the present application realizes efficient and stable operation of the charging process through multi-parameter collaborative monitoring and dynamic compensation mechanism. While ensuring the safety of charging, the running efficiency and stability of the liquid-cooled charging pile in different working conditions are significantly improved.

[0035] Empty line

[0036] In one embodiment of the present application, controlling the liquid-cooled charging pile to be in different working modes according to different conditions met by the second target parameter includes:

[0037] If the second target parameter meets the condition of the first working mode, the flow rate of the cooling liquid of the liquid-cooled charging pile is adjusted based on a first number of influence factors;

[0038] If the second target parameter meets the condition of the second working mode, the flow rate of the liquid-cooled charging pile is locked at a fixed value;

[0039] If the second target parameter meets the condition of the third working mode, the flow rate of the cooling liquid of the liquid-cooled charging pile is adjusted based on a second number of influence factors;

[0040] wherein the first number is less than the second number.

[0041] In the present embodiment, the first number of influence factors can be the implemented power, the temperature of the cooling liquid and the ambient temperature . Wherein the flow rate of the cooling liquid of the liquid-cooled charging pile is linearly positively correlated with the power as follows: wherein, .

[0042] Specifically, the determination of the coefficient may be based on the heat balance equation of the liquid cooling system, that is, the cooling liquid needs to take away the heat generated during the charging process, and the relationship can be expressed as: wherein, is the flow rate of the cooling liquid, is the power loss of the charging pile, usually 2%~5% of the charging power, is the density of the cooling liquid, is the specific heat capacity of the cooling liquid, is the allowable temperature rise of the cooling liquid. In the present application, the cooling liquid is a glycol water solution, and the power loss of the charging pile and the specific heat capacity of the cooling liquid are both empirical data.

[0043] In the present embodiment, the second working mode is a transition mode, and the fixed flow rate of the cooling liquid is the flow rate before switching the working mode, which can avoid the impact of flow rate mutation on the running state or heat dissipation effect of the equipment caused by mode switching, ensure smooth transition of the system from one working mode to another, and reduce the temperature fluctuation or fluid dynamic disturbance that may occur during the switching process, thereby improving the reliability and safety of the liquid-cooled charging pile during the mode switching stage.

[0044] In the present embodiment, the third working mode is a super following mode, and the flow rate of the cooling liquid of the liquid-cooled charging pile is adjusted by the second number of influence factors. The second number of influence factors can be the power mutation rate , power grid harmonics , thermal load prediction , and ambient temperature change rate and battery temperature .

[0045] Specifically, for the power mutation rate , its physical meaning is that when the power mutates, the thermal load will instantaneously increase, and the flow rate needs to be quickly increased to match the heat dissipation demand. The additional flow rate required for can be determined experimentally on a test platform. For example, a step change can be simulated on a 200kW charging pile platform, the temperature rise speed and the flow rate of the required cooling liquid are recorded, and it is experimentally determined that an additional 0.3L / min flow rate is required for each 1kW / s power mutation to maintain the allowable temperature rise of the cooling liquid <10 degrees Celsius.

[0046] In this embodiment, the grid harmonic can cause additional heat generation, such as increased IGBT switching loss, which requires an increase in heat dissipation capacity. According to existing data, it can be concluded that for each increase of 1%, the system loss rises by about 1.5%, so the flow rate of the cooling liquid needs to be adjusted according to .

[0047] In this embodiment, the thermal load prediction can be based on historical data to predict future thermal load, thereby adjusting the cooling liquid flow rate in advance.

[0048] Specifically, LSTM can be used to predict the thermal load . Based on the historical data of the previous 10 minutes, the sampling interval is set to 10 seconds, and 60 consecutive data samples are collected. For example, the charging power mutation rate, cooling liquid inlet and outlet temperature, ambient temperature sequence, and grid voltage fluctuation rate are sampled, and the sampled data is input into the LSTM, and the output result is the thermal load of the liquid-cooled charging pile in the next minute.

[0049] In this embodiment, the environmental temperature change rate and the battery temperature both have an impact on the liquid-cooled charging pile, which is determined experimentally. For example, for every increase in ambient temperature, the heat dissipation efficiency decreases by about 0.4% / min, so for every temperature rise, the flow rate needs to be increased by 0.5L / min. For the battery temperature, when the battery temperature is greater than , the life attenuation accelerates, and the measured result is that increasing the cooling liquid flow rate by 5L / min can increase the battery cooling rate by .

[0050] As can be seen from the above, the present application realizes the optimal balance of cooling efficiency and system stability through an intelligent parameter adjustment mechanism. The system dynamically switches between three working modes based on the second target parameter, significantly improving the response speed and temperature control accuracy of the liquid cooling system under dynamic load.

[0051] In an embodiment of the present application, the first working mode comprises:

[0052] Adjusting the cooling liquid flow rate of the liquid-cooled charging pile based on the matching relationship between the actual power and the optimal temperature of the cooling liquid of the liquid-cooled charging pile;

[0053] Adjusting the cooling liquid water pump power of the liquid-cooled charging pile based on PID.

[0054] In the embodiment, the first working mode is a normal following mode, which is the basic control strategy of the liquid-cooled supercharging system and is suitable for steady state or small amplitude fluctuation working conditions. The core is to realize the dynamic adjustment of the liquid cooling flow rate through power-temperature matching control and PID control.

[0055] Specifically, first, the power-temperature matching relationship can be constructed, the theoretical flow demand can be calculated according to the mapping relationship between the actual charging power and the optimal temperature of the cooling liquid, and therefore the cooling liquid flow rate can be quickly adjusted. Second, the PID fine adjustment control can be used to adjust the water pump power through feedback to ensure that the cooling liquid temperature is stable in the target range. For example, Table 1 is a power-temperature preset matching table constructed according to experimental data.

[0056] Table 1 Preset matching table

[0057]

[0058] In the embodiment, the parameters input into the PID adjustment controller can be the deviation of the real-time temperature of the cooling liquid from the target temperature , and the output is the adjustment amount of the cooling liquid water pump of the liquid-cooled charging pile . Specifically, the PID is realized by the formula

[0059] Among them, the proportional term can quickly respond to the temperature deviation; the integral term can eliminate the steady-state error; can suppress overshoot; is the current time; is the sampling time; the above data are obtained by experiment.

[0060] ​From the above, the liquid-cooled charging pile ordinary following mode control system proposed in the application realizes efficient temperature control in a steady state working condition through the dual mechanisms of power-temperature matching and PID adjustment. The theoretical flow demand is quickly determined through the mapping relationship between the charging power and the optimal temperature of the cooling liquid, and a PID controller is used for accurate fine tuning. This combined control strategy not only ensures the rapid flow adjustment capability when the power changes, but also ensures the accurate real-time control of the cooling liquid temperature through the closed-loop feedback mechanism of the PID, so that the system can maintain the optimal working temperature in a steady state or small amplitude fluctuation working condition, thereby providing a basic and reliable thermal management scheme for the liquid-cooled charging pile.

[0061] In an embodiment of the application, when the liquid-cooled charging pile is switched from the first working mode to the second working mode, the flow in the second working mode is the flow in the first working mode.

[0062] In this embodiment, when the liquid-cooled charging pile receives a signal for mode switching, it enters a transition mode from the ordinary following mode, and at this time the flow of the cooling liquid is fixed in the ordinary mode. The above operation can avoid thermal shock, mechanical stress and control oscillation caused by sudden change of flow, thereby protecting the safe operation of the liquid-cooled charging pile and increasing its service life.

[0063] Specifically, sudden change of cooling liquid flow rate can cause local overheating or overcooling. On the one hand, when the flow suddenly decreases, the residence time of the cooling liquid in the heat generating components (such as power modules) is prolonged, causing heat accumulation. For example, if the flow suddenly decreases from 30 L / min to 15 L / min, the heat dissipation capacity instantaneously decreases by 50%, and the insulated gate bipolar transistor junction temperature may rise by more than 20°C, which can easily cause damage. On the other hand, when the flow suddenly increases, the low-temperature cooling liquid is concentrated in the high-temperature area for a short time, causing material thermal stress. For example, copper bars produce microcracks due to a temperature gradient > 10°C / mm.

[0064] For mechanical stress, water hammer effect is easy to occur in the pipeline when the flow suddenly changes, and the fluid inertia causes the pipeline pressure fluctuation to reach 3 times the rated pressure. The sudden change of pump speed can cause axial movement, shorten the service life of mechanical seals and cause bearing wear.

[0065] For control oscillation, when the flow set value suddenly changes, the PID controller is easy to cause severe oscillation, and the overshoot can reach 30%.

[0066] From the above, the mode switching control mechanism proposed in the application effectively solves the system stability problem in the working mode switching process of the liquid-cooled charging pile through the flow retention strategy. When the system switches from the normal following mode to the transition mode, the cooling liquid flow maintains the value before switching, which has three protection effects: in terms of thermal management, it avoids local overheating caused by flow mutation; in terms of mechanical protection, it prevents water hammer effect and mechanical component wear; in terms of control stability, it eliminates the oscillation risk of the PID regulator. The transition mode freezes the flow parameter, allowing the system to smoothly transition while maintaining the original cooling capacity, ensuring the safe operation of key components and creating a stable thermodynamic environment for subsequent mode switching, significantly improving the reliability and service life of the liquid-cooled charging pile.

[0067] In an embodiment of the application, the third working mode includes:

[0068] Based on historical data, predict the thermal load change of the liquid-cooled charging pile in the next cycle to obtain first prediction data;

[0069] Based on historical data, predict the power change of the liquid-cooled charging pile in the next cycle to obtain second prediction data;

[0070] Based on the first prediction data and the second prediction data, a dynamic weight adjustment strategy is constructed to compensate for the key parameters in the second target parameter.

[0071] In this embodiment, the third working mode is an advanced control strategy for the liquid-cooled charging pile to deal with extreme dynamic conditions such as power surges and environmental changes. Its core innovation lies in the double prediction mechanism and dynamic weight compensation. For the double prediction mechanism, it can simultaneously predict the thermal load and power change , covering electrical and thermal coupling, and for dynamic weight compensation, it adjusts parameter weights in real time according to prediction confidence to avoid control failure caused by single prediction deviation.

[0072] Specifically, LSTM can be used to predict the thermal load Prediction is made. Based on the historical data of the past 10 minutes, the sampling interval is set to 10 seconds, and 60 consecutive data samples are collected. First, the past 10 minutes of data are extracted in a rolling manner, including sampling the charging power mutation rate, the cooling liquid inlet and outlet temperature, the ambient temperature sequence, and the power grid voltage fluctuation rate. Second, data augmentation can be performed by adding Gaussian noise in the data preprocessing stage. For example, for each sample in the original data, a noise value is randomly generated with a mean of 0 and a standard deviation of 1% Gaussian distribution, which is superimposed on the feature dimension of the original data to form a noisy augmented sample. This method simulates the noise interference that may exist in the real scene, such as sensor measurement error and signal transmission interference, forcing the model to learn the essential features of the data rather than surface details, thereby enhancing the model's generalization ability in the presence of environments, reducing the risk of overfitting, and making the trained model more adaptable to non-ideal data in actual application. Finally, the processed data is input into the LSTM prediction model to obtain the predicted data.

[0073] In this embodiment, the core of dynamic weight compensation is to dynamically adjust the influence weight of different parameters on the final control instruction according to the real-time confidence of the predicted data.

[0074] Specifically, the technical logic can be divided into three steps: confidence evaluation, weight allocation, and compensation execution. For example, confidence evaluation can quantify the reliability of each prediction parameter; weight allocation can allocate parameter weights in proportion to confidence; and compensation execution can strengthen compensation for high-weight parameters.

[0075] As can be seen from the above, the third working mode proposed in the present application improves the control accuracy of the liquid-cooled charging pile in extreme dynamic conditions through the innovative double-prediction mechanism and dynamic compensation strategy. The system uses an LSTM neural network to build a double-prediction engine, which not only ensures the coordinated control of the electrical-thermal coupled system, but also effectively reduces the risk of single prediction bias through noise injection and confidence evaluation. This allows the system to maintain a temperature control accuracy of ±1℃ in extreme conditions such as power mutations and environmental sudden changes, with a significant improvement in response speed compared to traditional methods.

[0076] In an embodiment of the present application, the first target parameter is compensated based on the ambient temperature of the environment in which the liquid-cooled charging pile is located to obtain a second target parameter, comprising:

[0077] The ambient temperature of the environment in which the liquid-cooled charging pile is located and the first target parameter are input into a first neural network for data augmentation to obtain a second target parameter.

[0078] In this embodiment, the first neural network can adopt an LSTM neural network. This application adopts an LSTM neural network to realize dynamic compensation of charging parameters by ambient temperature. The core of the LSTM neural network is to learn the temporal correlation between ambient temperature and charging parameters through historical temperature data, thereby generating a second target parameter that is more suitable for actual working conditions.

[0079] Specifically, LSTM can capture the lag effects of ambient temperature changes, such as cooling systems after sustained high temperatures, thereby modeling temporal dependencies. Secondly, it can simultaneously handle the complex relationships between temperature and parameters such as power, flow, and voltage thresholds, avoiding the limitations of traditional linear formulas. Finally, by training the model with historical data, it can adapt to the compensation needs of different climate regions, such as hot and dry areas and high-humidity coastal areas.

[0080] For example, temperature data can be sampled in a continuous time window. The sampled data and the first target parameter value are then preprocessed, including normalization and filtering for abnormal data. An LSTM input vector is constructed based on the preprocessed data, and compensation parameters are obtained. Finally, the compensation parameters are denormalized to generate the second target parameter.

[0081] As can be seen from the above, the temperature compensation method proposed in this application achieves intelligent coupling of environmental parameters and charging system parameters through an LSTM neural network. Compared with traditional linear formulas, this deep learning-based compensation method improves the accuracy of temperature adaptive control by 40%. In particular, under extreme temperature fluctuation conditions, such as temperature changes exceeding 10°C within 5 minutes, the system response speed is improved by more than 50%, reducing the impact of nonlinear coupling between ambient temperature and electrical parameters.

[0082] Corresponding to the liquid-cooled supercharge charging control method of the above embodiment, Figure 2 This is a structural block diagram of a liquid-cooled supercharge control device provided in one embodiment of the present application. For ease of illustration, only the parts related to the embodiment of the present application are shown. Figure 2 The liquid-cooled supercharge control device 20 includes: a data acquisition module 21, a data expansion module 22, and a power adjustment module 23.

[0083] The data acquisition module 21 is configured to obtain first target parameters of the liquid-cooled charging pile, the first target parameters including operating parameters of the liquid-cooled charging pile and grid parameters of the grid where the liquid-cooled charging pile is located;

[0084] A data expansion module 22 is configured to compensate the first target parameter based on the ambient temperature of the environment in which the liquid-cooled charging pile is located to obtain a second target parameter;

[0085] The power adjustment module 23 is configured to control the liquid-cooled charging pile to be in different working modes according to different conditions of the second target parameter, wherein the liquid-cooled parameters of the liquid-cooled charging pile are different when the liquid-cooled charging pile is in different working modes.

[0086] In an embodiment of the present application, the power adjustment module 23 is specifically configured to: if the second target parameter meets the condition of the first working mode, adjust the flow of the cooling liquid of the liquid-cooled charging pile based on the first number of influence factors;

[0087] If the second target parameter meets the condition of the second working mode, the flow of the liquid-cooled charging pile is locked at a fixed value.

[0088] If the second target parameter meets the condition of the third working mode, adjust the flow of the cooling liquid of the liquid-cooled charging pile based on the second number of influence factors.

[0089] In an embodiment of the present application, the power adjustment module 23 is specifically configured to: adjust the flow of the cooling liquid of the liquid-cooled charging pile based on the matching relationship between the actual power and the optimal temperature of the cooling liquid of the liquid-cooled charging pile.

[0090] The cooling liquid pump power of the liquid-cooled charging pile is adjusted based on PID.

[0091] In an embodiment of the present application, the power adjustment module 23 is specifically configured to:

[0092] When the liquid-cooled charging pile is switched from the first working mode to the second working mode, the flow in the second working mode is the flow in the first working mode.

[0093] In an embodiment of the present application, the power adjustment module 23 is specifically configured to:

[0094] When the liquid-cooled charging pile is switched from the third working mode to the second working mode, the flow in the second working mode is the flow in the third working mode.

[0095] In an embodiment of the present application, the power adjustment module 23 is specifically configured to:

[0096] Based on historical data, predict the thermal load change of the liquid-cooled charging pile in the next cycle to obtain first prediction data;

[0097] Based on historical data, predict the power change of the liquid-cooled charging pile in the next cycle to obtain second prediction data;

[0098] Based on the first prediction data and the second prediction data, a dynamic weight adjustment strategy is constructed to compensate for the key parameters in the second target parameter.

[0099] In an embodiment of the present application, the power adjustment module 23 is specifically configured to:

[0100] The ambient temperature of the environment in which the liquid-cooled charging pile is located and the first target parameter are input into the first neural network for data expansion to obtain the second target parameter.

[0101] See also Figure 3 , Figure 3 This is a schematic block diagram of an electronic device provided in one embodiment of the present application. Figure 3 The electronic device 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memory 304 is used to store computer programs, which include program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. The processor 301 is configured to call the program instructions to execute the functions of the modules / units in the above-mentioned device embodiments, such as Figure 2 The functions of the data acquisition module 21, the data expansion module 22 and the power adjustment module 23 are shown.

[0102] It should be understood that in the embodiment of the present application, the processor 301 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0103] The input device 302 may include a touchpad, a fingerprint collection sensor (for collecting user fingerprint information and fingerprint direction information), a microphone, etc. The output device 303 may include a display (LCD, etc.), a speaker, etc.

[0104] The memory 304 may include a read-only memory and a random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include a nonvolatile random access memory.

[0105] In specific implementations, the processor 301, the input device 302, and the output device 303 described in the embodiments of the present application can execute the implementation manners of the liquid-cooled supercharging charging control method provided by the embodiments of the present application, and can also execute the implementation manners of the electronic device described in the embodiments of the present application, which will not be described here.

[0106] In another embodiment of the present application, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. The computer program includes program instructions, and the program instructions are executed by a processor to implement all or part of the processes of the above-mentioned embodiment methods. The computer program can also be used to instruct related hardware to complete, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiments can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms. The computer readable medium can include any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium.

[0107] The computer readable storage medium can be an internal storage unit of the electronic device of any of the above-mentioned embodiments, such as a hard disk or a memory of the electronic device. The computer readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, and the like. Further, the computer readable storage medium can include both the internal storage unit and the external storage device of the electronic device. The computer readable storage medium is used to store the computer program and other programs and data required by the electronic device. The computer readable storage medium can also be used to temporarily store data that has been output or will be output.

[0108] The embodiments of the present application provide a computer program product, which includes computer executable instructions or a computer program. The computer executable instructions or the computer program are stored in a computer readable storage medium. A processor of an electronic device reads the computer executable instructions from the computer readable storage medium. The processor executes the computer executable instructions, so that the electronic device executes the liquid-cooled supercharging charging control method described in the embodiments of the present application.

[0109] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, the specific working process of the electronic device and the units described above can refer to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0110] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, the specific working process of the electronic device and the units described above can refer to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0111] In several embodiments provided in the present application, it should be understood that the disclosed electronic device and method can be implemented in other ways. For example, the above-described device embodiments are only schematic, for example, the division of units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface or unit, and can also be electrical, mechanical or other forms of connection.

[0112] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0113] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0114] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A liquid-cooled supercharge control method, characterized in that: include: Acquire first target parameters of the liquid-cooled charging pile, where the first target parameters include operating parameters of the liquid-cooled charging pile and grid parameters of a grid where the liquid-cooled charging pile is located; Compensating the first target parameter based on the ambient temperature of the environment in which the liquid-cooled charging pile is located to obtain a second target parameter; controlling the liquid-cooled charging pile to operate in different operating modes according to different conditions satisfied by the second target parameter, wherein the liquid cooling parameters of the liquid-cooled charging pile are different when the liquid-cooled charging pile is in different operating modes; The controlling the liquid-cooled charging pile to operate in different operating modes according to the second target parameter satisfying different conditions includes: If the second target parameter satisfies the condition of the first working mode, adjusting the flow rate of the coolant of the liquid-cooled charging pile based on the first number of influencing factors; If the second target parameter meets the conditions of the second working mode, locking the flow rate of the liquid-cooled charging pile at a fixed value; If the second target parameter satisfies the conditions of the third working mode, adjusting the coolant flow of the liquid-cooled charging pile based on a second number of influencing factors; wherein the first number is less than the second number; The first working mode includes: Adjusting the coolant flow rate of the liquid-cooled charging pile based on a matching relationship between actual power and an optimal temperature of the coolant of the liquid-cooled charging pile; Adjusting the coolant pump power of the liquid-cooled charging pile based on PID; The third working mode includes: Predicting the heat load change of the liquid-cooled charging pile in the next cycle based on historical data to obtain first prediction data; Predicting the power change of the liquid-cooled charging pile in the next cycle based on historical data to obtain second prediction data; A dynamic weight adjustment strategy is constructed based on the first prediction data and the second prediction data to compensate for key parameters in the second target parameters.

2. The liquid-cooled supercharge control method according to claim 1, wherein: When the liquid-cooled charging pile switches from the first working mode to the second working mode, the flow rate in the second working mode is the flow rate in the first working mode.

3. The liquid-cooled supercharge control method according to claim 1, wherein: When the liquid-cooled charging pile switches from the third working mode to the second working mode, the flow rate in the second working mode is the flow rate in the third working mode.

4. The liquid-cooled supercharge control method according to claim 1, wherein: The compensating the first target parameter based on the ambient temperature of the environment in which the liquid-cooled charging pile is located to obtain the second target parameter includes: The ambient temperature of the environment in which the liquid-cooled charging pile is located and the first target parameter are input into the first neural network for data expansion to obtain the second target parameter.

5. A liquid-cooled supercharge control device, characterized in that: include: a data acquisition module, configured to acquire first target parameters of the liquid-cooled charging pile, the first target parameters including operating parameters of the liquid-cooled charging pile and grid parameters of a grid where the liquid-cooled charging pile is located; a data expansion module, configured to compensate the first target parameter based on the ambient temperature of the environment in which the liquid-cooled charging pile is located to obtain a second target parameter; a power adjustment module, configured to control the liquid-cooled charging pile to operate in different operating modes according to the second target parameter satisfying different conditions, wherein the liquid cooling parameters of the liquid-cooled charging pile are different when the liquid-cooled charging pile is in different operating modes; The power adjustment module is specifically configured to: if the second target parameter satisfies the condition of the first working mode, adjust the flow rate of the coolant of the liquid-cooled charging pile based on the first number of influencing factors; If the second target parameter meets the conditions of the second working mode, the flow rate of the liquid-cooled charging pile is locked at a fixed value; If the second target parameter satisfies the conditions of the third working mode, adjusting the coolant flow of the liquid-cooled charging pile based on the second number of influencing factors; wherein the first number is less than the second number; The power adjustment module is specifically used to: adjust the coolant flow rate of the liquid-cooled charging pile based on the matching relationship between the actual power and the optimal temperature of the coolant of the liquid-cooled charging pile; PID-based adjustment of the coolant pump power of the liquid-cooled charging pile; The power adjustment module is specifically used for: Predicting the heat load change of the liquid-cooled charging pile in the next cycle based on historical data to obtain first prediction data; Predicting the power change of the liquid-cooled charging pile in the next cycle based on historical data to obtain second prediction data; A dynamic weight adjustment strategy is constructed based on the first prediction data and the second prediction data to compensate for key parameters in the second target parameters.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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