Liquid cooling partition intelligent control method for energy storage system

Abstract

The invention provides a liquid cooling partition intelligent control method for an energy storage system, and relates to the technical field of intelligent control, and the method comprises the steps: obtaining the real-time operation data of the energy storage system, and analyzing the current heat demand of the energy storage system based on the temperature data of an energy storage converter and a battery pack; a real-time temperature control target is determined, then a liquid cooling working mode is selected, a corresponding liquid cooling control instruction is generated, the operation rotating speed of a water pump of the water cooling unit is adjusted according to the instruction, corresponding cooling liquid flow is generated, cooling liquid is distributed to an energy storage converter and a battery pack loop by adjusting and controlling the opening and closing angle of a three-way valve, and an initial liquid cooling path is formed; cooling simulation and optimization are carried out by establishing a real-time twinborn model, the problems that the energy efficiency is low and the system performance is unstable due to the fact that dynamic and independent refrigeration control cannot be provided for different thermal load requirements through liquid cooling and heating management are solved, and the effects of improving the thermal management efficiency and the system energy utilization efficiency and optimizing the system stability are achieved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to a liquid cooling partition intelligent control method for an energy storage system. Background Art

[0002] Thermal management is one of the key technologies in modern energy storage systems, especially for systems involving power storage converters (PCS) and battery packs. Liquid cooling technology is one of the most widely used heat dissipation methods. This technology removes heat through flowing coolant to help keep the temperature of system equipment within a safe and efficient operating range. Traditional liquid cooling systems usually use a single loop to connect the PCS and battery packs in the same cooling loop. This configuration is simple and low-cost, but due to the large difference in thermal loads between PCS and batteries, it is difficult to effectively distribute heat and accurately control the temperature, which often leads to low system efficiency and high energy consumption. In addition, existing liquid cooling management systems usually lack flexibility and adaptability when dealing with complex thermal loads, and cannot adjust cooling requirements based on real-time data. In this case, the optimal thermal management performance cannot be guaranteed, especially under changing operating conditions and different load requirements. Therefore, liquid cooling management systems often face a contradiction between cooling performance and energy efficiency, and it is difficult to simultaneously meet system performance stability and economic benefits.

[0003] In summary, existing liquid cooling thermal management cannot provide dynamic and independent cooling control for different heat load requirements, resulting in technical problems such as low energy efficiency and unstable system performance. Summary of the invention

[0004] The present application provides a liquid cooling partition intelligent control method for an energy storage system, which is used to solve the technical problem that the existing liquid cooling thermal management cannot provide dynamic and independent refrigeration control for different heat load requirements, resulting in low energy efficiency and unstable system performance.

[0005] The present application provides a liquid cooling partition intelligent control method for an energy storage system, the method comprising:

[0006] Acquire real-time operation data of the energy storage system, including temperature data of the energy storage inverter and the battery pack, wherein the temperature data of the energy storage inverter is collected by the inverter temperature sensor, and the temperature data of the battery pack is collected by the battery temperature sensor; based on the temperature data of the energy storage inverter and the temperature data of the battery pack, analyze the current heat demand of the energy storage system and determine the real-time temperature control target; according to the real-time temperature control target, select the liquid cooling working mode through the energy management system, and the liquid cooling working mode includes single PCS cooling mode, single battery cooling mode, dual-circuit cooling mode and full-closed mode, and generate corresponding liquid cooling control instructions; according to the liquid cooling control instructions, adjust the operating speed of the water pump of the water cooling unit to generate a coolant flow matching the current liquid cooling working mode; based on the coolant flow, distribute the coolant to the energy storage inverter circuit and the battery pack circuit by adjusting the opening and closing angle of the three-way valve to form an initial liquid cooling path; by establishing a real-time twin model, perform cooling simulation based on the initial liquid cooling path, optimize the coolant flow according to the simulation results, and generate an optimized liquid cooling control scheme; according to the optimized liquid cooling control scheme, perform liquid cooling control.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] The present application provides a liquid cooling partition intelligent control method for an energy storage system, which obtains real-time operating data of the energy storage system, including temperature data of the energy storage inverter and the battery pack, wherein the temperature data of the energy storage inverter is collected by the inverter temperature sensor, and the temperature data of the battery pack is collected by the battery temperature sensor; based on the temperature data of the energy storage inverter and the temperature data of the battery pack, the current heat demand of the energy storage system is analyzed to determine the real-time temperature control target; according to the real-time temperature control target, a liquid cooling working mode is selected through an energy management system, and the liquid cooling working mode includes a single PCS cooling mode, a single battery cooling mode, a dual-circuit cooling mode and a full-off mode, and a corresponding liquid cooling control instruction is generated; according to the liquid cooling control instruction, the water cooling is adjusted The operating speed of the unit's water pump generates a coolant flow that matches the current liquid cooling working mode; based on the coolant flow, the coolant is distributed to the energy storage inverter circuit and the battery pack circuit by adjusting the opening and closing angle of the three-way valve to form an initial liquid cooling path; by establishing a real-time twin model, a cooling simulation is performed based on the initial liquid cooling path, and the coolant flow is optimized according to the simulation results to generate an optimized liquid cooling control scheme; according to the optimized liquid cooling control scheme, liquid cooling control is executed, which solves the technical problem that the existing liquid cooling thermal management cannot provide dynamic and independent refrigeration control for different heat load requirements, resulting in low energy efficiency and unstable system performance, and achieves the technical effect of improving thermal management efficiency and system energy utilization efficiency and optimizing system stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic flow chart of a liquid cooling partition intelligent control method for an energy storage system is provided for this application.

[0010] Figure 2 The present application provides a flow chart for determining real-time temperature control targets in a liquid cooling partition intelligent control method for an energy storage system. DETAILED DESCRIPTION

[0011] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0012] Examples, such as Figure 1 As shown, the present application provides a liquid cooling partition intelligent control method for an energy storage system, the method comprising:

[0013] Acquire real-time operation data of the energy storage system, including temperature data of the energy storage converter and the battery pack, wherein the temperature data of the energy storage converter is collected by the converter temperature sensor, and the temperature data of the battery pack is collected by the battery temperature sensor.

[0014] Specifically, real-time operation data includes temperature data of the energy storage converter (PCS) and battery pack, and the accurate acquisition of these data is completed through special sensors. The acquisition of temperature data of the energy storage converter is realized through converter temperature sensors. These sensors are usually installed at key hot spots of the converter, such as near electronic components or heat sinks, and can sense and record the temperature of the converter during operation. The selection of this installation location is based on the working characteristics and heat dissipation requirements of the converter to ensure the authenticity and practicality of the data. Battery pack temperature data is collected through battery temperature sensors. These sensors are usually arranged between battery cells or battery modules. The selection of key locations is intended to monitor the thermal changes of the battery during charging and discharging, because these changes directly affect the performance and safety of the battery. Battery temperature sensors can provide the temperature status of the battery in real time, which is crucial to prevent overheating and maintain battery efficiency. Through these special sensors, accurate PCS and battery pack temperature data can be obtained in real time, and these data are then transmitted to the central processing unit or energy management system (EMS), which is then used to analyze the current heat demand and as a basis for adjusting the working mode of the liquid cooling system. For example, if the sensor reports that the temperature of the PCS exceeds the preset safety threshold, the EMS will immediately adjust the liquid cooling system and increase the coolant flow to the PCS to prevent overheating and maintain stable operation of the system. This precise collection of real-time data and immediate response ensures that the energy storage system can achieve the best thermal management efficiency and safety standards under any operating conditions. Through such a setting, the overall performance and economic benefits of the energy storage system can be effectively improved, while also significantly reducing energy consumption and operating costs.

[0015] Based on the energy storage converter temperature data and the battery pack temperature data, the current heat demand of the energy storage system is analyzed to determine the real-time temperature control target.

[0016] According to the real-time temperature control target, the liquid cooling working mode is selected through the energy management system, and the liquid cooling working mode includes single PCS cooling mode, single battery cooling mode, dual-circuit cooling mode and full-off mode, and the corresponding liquid cooling control instructions are generated.

[0017] Optionally, following the acquisition of real-time operating data, the next step is to conduct an in-depth analysis of the current heat demand of the energy storage system based on the obtained temperature data of the energy storage converter (PCS) and the battery pack, so as to determine the real-time temperature control target. The temperature data involved in the analysis process is provided by the aforementioned sensor system, which ensures the accuracy and real-time nature of the analysis. First, the system evaluates the current thermal state and cooling requirements of the PCS and the battery pack by analyzing their real-time temperature data. For example, if the temperature data of the PCS is higher than the preset safe operating range, it indicates that additional cooling is required to avoid overheating. At this time, the temperature control target is to adjust the temperature of the PCS back to the safe range. Similarly, temperature monitoring of the battery pack is equally important, because overheating or overcooling of the battery will affect its performance and life. Next, based on the analysis results and the set real-time temperature control target, the energy management system (EMS) will select the most appropriate liquid cooling working mode to meet the current thermal management needs. EMS plays a vital role in this link. It automatically selects one of the four liquid cooling working modes based on the input temperature data and the preset response strategy. The four liquid cooling working modes include single PCS cooling mode, single battery cooling mode, dual-circuit cooling mode and full shutdown mode. Among them, the single PCS cooling mode means that it is enabled only when the temperature of the PCS exceeds the standard and the temperature of the battery pack is normal; the single battery cooling mode means that it is enabled only when the temperature of the battery pack exceeds the standard and the temperature of the PCS is normal; the dual-circuit cooling mode means that it is enabled when the temperature of the PCS and the battery pack exceeds the standard at the same time; the full shutdown mode means that it is enabled when the temperature of the PCS and the battery pack is within the normal range to save energy and reduce operating costs. The selection of each mode is based on the principle of maximizing thermal efficiency and energy efficiency. After the selection is completed, the EMS will generate corresponding liquid cooling control instructions to adjust the operation of the liquid cooling system, such as adjusting the speed of the water pump, opening and closing related valves, etc., to achieve precise temperature control. These control instructions directly affect the response and performance of the liquid cooling system, ensuring that the energy storage system can operate under the optimal thermal management conditions at any given moment. In this way, not only the operating efficiency of the energy storage system is optimized, but also energy consumption and maintenance requirements are reduced, greatly enhancing the reliability and economy of the system. This series of analysis and response mechanisms ensure that the energy storage system can maintain optimal performance under various operating conditions.

[0018] According to the liquid cooling control instruction, the operating speed of the water pump of the water cooling unit is adjusted to generate a coolant flow that matches the current liquid cooling working mode.

[0019] Based on the coolant flow rate, the coolant is distributed to the energy storage inverter circuit and the battery pack circuit by adjusting the opening and closing angle of the three-way valve to form an initial liquid cooling path.

[0020] Exemplarily, adjusting the operating speed of the water pump of the water cooling unit according to the liquid cooling control instruction is a key step to achieve precise temperature control. In this process, the speed adjustment of the water pump directly determines the size of the coolant flow, which in turn affects the thermal management efficiency of the entire energy storage system. At this stage, the energy management system (EMS) generates corresponding liquid cooling control instructions according to the previously set liquid cooling working mode. These instructions specify the speed that the water pump should reach to ensure sufficient coolant flow to meet the real-time cooling needs of the energy storage converter (PCS) and the battery pack. For example, if the selected liquid cooling mode is a single PCS cooling mode, the operating speed of the water pump will be adjusted to generate sufficient coolant flow only for PCS use, without oversupply, so as to improve energy efficiency and cooling efficiency. Similarly, in the dual-circuit cooling mode, the water pump speed will increase to provide sufficient flow to meet the cooling needs of the PCS and the battery pack at the same time. Next, based on the generated coolant flow, the coolant is distributed to the energy storage converter circuit and the battery pack circuit by adjusting the opening and closing angle of the three-way valve to form an initial liquid cooling path. During this process, the three-way valve precisely controls the opening and closing of each channel, allowing the coolant to flow along a predetermined path to ensure maximum cooling effect. The operation of adjusting the three-way valve is based on the aforementioned liquid cooling control instructions and the results of the coolant flow calculation to ensure that each system part receives the appropriate amount of coolant to keep the operating temperature within the optimal range. Through this comprehensive control strategy, not only the cooling process is optimized, but also the maximum efficiency of energy use is achieved. The precise distribution and flow control of the coolant allows the energy storage system to maintain the optimal temperature under different load conditions, thereby improving the overall performance and reliability of the system. This approach ensures high efficiency and long-term stability of the system under all operating conditions, significantly reducing maintenance requirements and operating costs.

[0021] By establishing a real-time twin model, a cooling simulation is performed based on the initial liquid cooling path, the coolant flow is optimized according to the simulation results, and an optimized liquid cooling control solution is generated.

[0022] Liquid cooling control is performed according to the optimized liquid cooling control scheme.

[0023] Specifically, the real-time twin model is an advanced simulation tool that replicates the physical characteristics and operating status of the system based on real-time data. This model accurately maps the liquid cooling path of the energy storage system in the digital space, including the thermal response characteristics of the energy storage converter (PCS) and the battery pack. First, a cooling simulation based on the initial liquid cooling path is performed by the real-time twin model. The initial liquid cooling path refers to the flow route of the coolant in the system according to the previously determined liquid cooling control instructions and water pump adjustments. The model takes these paths as input and simulates the heat exchange efficiency and temperature changes when the coolant flows in these paths. This simulation process not only considers the flow rate of the coolant, but also the flow rate, temperature, and the heat transfer characteristics involved. Next, the coolant flow rate is optimized based on the simulation results. This process involves analyzing the simulation data to determine whether the existing coolant flow rate is sufficient to meet the temperature control requirements, or whether there is energy waste caused by excessive cooling. If the simulation shows that the existing flow setting fails to effectively control the temperature or the efficiency is not optimal, the model will recommend adjusting the flow rate to more accurately match the actual heat load requirements. Then, an optimized liquid cooling control scheme is generated, which includes detailed parameters such as the adjusted coolant flow rate, water pump speed, and the opening and closing angle of the three-way valve. This optimization scheme is based on real-time data and simulation results, and aims to achieve the best thermal management effect and energy efficiency. Finally, liquid cooling control is performed according to the optimized liquid cooling control scheme, which means that the energy management system (EMS) will automatically adjust the operating parameters of the water pump and the configuration of the valve, and implement the distribution of coolant according to the optimized scheme. This step ensures that the energy storage system can operate with optimal thermal efficiency in all operating stages, while also reducing equipment losses and failures that may be caused by improper thermal management. Through this series of control steps, it is ensured that the liquid cooling management of the energy storage system is both efficient and energy-saving, optimizes the overall performance and reliability of the system, and effectively extends the service life of the equipment.

[0024] Furthermore, if Figure 2 As shown, based on the energy storage converter temperature data and the battery pack temperature data, the current heat demand of the energy storage system is analyzed to determine the real-time temperature control target, including:

[0025] The temperature data of the energy storage inverter is compared with the preset temperature control range, and the heat demand of the energy storage inverter is determined according to the comparison result; the temperature data of the battery pack is compared with the battery safety temperature range, and the heat demand of the battery pack is determined according to the comparison result; based on the heat demand of the energy storage inverter and the heat demand of the battery pack, the real-time temperature control targets of the energy storage inverter and the battery pack are determined respectively.

[0026] Furthermore, for the energy storage converter, its temperature data is collected by temperature sensors installed at key heat generation points, and this data is compared with the preset temperature control range to evaluate whether the PCS is operating in its optimal temperature range. For example, if the actual temperature of the PCS exceeds the preset maximum safety temperature threshold, this indicates that the PCS needs more cooling to maintain its performance and avoid damage caused by overheating. At this time, the temperature control system will be triggered to increase the cooling intensity and adjust the settings of the liquid cooling system to ensure that the temperature returns to the safe range. Next, for the battery pack, its temperature data is collected in a similar way, but the focus is on ensuring that the battery does not exceed its safe temperature range, which is critical to the life and performance of the battery. The temperature of the battery pack is compared with the preset safety temperature range. If the battery temperature is too high or too low, it will trigger the temperature control system to make corresponding adjustments. Low temperature may cause the battery reaction rate to decrease, while high temperature may cause chemical instability and increase safety risks. Through these comparison results, the system can determine a real-time temperature control target for each PCS and battery pack. These targets are set based on their respective heat requirements to ensure that each component can operate at its ideal operating temperature. For example, if the PCS needs to cool down and the battery pack needs to maintain the current temperature, the system will adjust the liquid cooling control strategy accordingly, which may be to increase the cooling flow of the PCS while keeping the flow of the battery pack unchanged. In addition, the setting of temperature control targets is not only based on a single temperature reading, but also continuously monitors temperature changes and responds to temperature fluctuations through dynamic adjustments, thereby providing continuous temperature management. This approach ensures that the energy storage system can maintain the optimal temperature throughout the entire operating cycle, thereby maximizing system efficiency, extending equipment life, and reducing maintenance costs.

[0027] Furthermore, according to the real-time temperature control target, a liquid cooling working mode is selected through the energy management system, and the liquid cooling working mode includes a single PCS cooling mode, a single battery cooling mode, a dual-circuit cooling mode and a full-off mode, and a corresponding liquid cooling control instruction is generated, including:

[0028] When the real-time temperature control target only needs to perform temperature control on the energy storage inverter, the single PCS cooling mode is selected to generate a liquid cooling control instruction for opening the PCS loop valve and closing the battery loop valve; when the real-time temperature control target only needs to perform temperature control on the battery pack, the single battery cooling mode is selected to generate a liquid cooling control instruction for opening the battery loop valve and closing the PCS loop valve; when the real-time temperature control target needs to perform temperature control on both the energy storage inverter and the battery pack, the dual-loop cooling mode is selected to generate a liquid cooling control instruction for simultaneously opening the PCS loop valve and the battery loop valve; when the real-time temperature control target does not need to perform temperature control, the full-close mode is selected to generate a liquid cooling control instruction for closing all valves.

[0029] In a specific embodiment, when the real-time temperature control target indicates that the energy storage converter needs to be temperature controlled separately, the EMS selects the single PCS cooling mode. In this mode, the control instructions generated by the EMS instruct the liquid cooling system to open the valve of the PCS loop and close the valve to the battery pack, which ensures that all coolant is directed to the PCS, thereby providing the necessary cooling to maintain its temperature within a safe and effective operating range. This mode is particularly suitable for situations where the PCS is working under high load and the battery pack does not require additional cooling. Next, if the real-time temperature control target shows that only the battery pack needs temperature control, the EMS will select the single battery cooling mode. In this case, the generated liquid cooling control instructions will instruct to open the valve of the battery loop and close the valve of the PCS loop. This measure ensures that the coolant flows only to the battery pack, providing cooling for it, helping the battery maintain its ideal operating temperature, thereby optimizing its performance and extending its service life. When the real-time temperature control target indicates that both the PCS and the battery pack need temperature control, the EMS will select the dual-loop cooling mode. Instructions in this mode will cause the valves of the PCS and the battery pack to open at the same time, allowing coolant to flow to these two key components at the same time. This mode is used when both are under high heat load or environmental conditions require cooling at the same time to ensure the optimization of the overall system performance. When the real-time temperature control target shows that neither the PCS nor the battery pack requires additional temperature control, that is, when their temperatures are ideal, the EMS will select the full shutdown mode. In this mode, the valves of all liquid cooling circuits will be closed, which not only saves energy, but also reduces system wear and tear and extends the service life of the equipment. This mode is very effective when the system is idle or external temperature conditions permit. In this way, it is possible to ensure that each component in the energy storage system can operate at its optimal temperature, thereby optimizing the performance and efficiency of the entire system. At the same time, this flexible temperature control strategy also helps to reduce operating costs and improve system reliability and safety.

[0030] Furthermore, according to the liquid cooling control instruction, the operating speed of the water pump of the water cooling unit is adjusted to generate a coolant flow matching the current liquid cooling working mode, including:

[0031] When the liquid cooling control instruction is a single PCS cooling mode, the water pump of the water cooling unit is adjusted to an operating speed that meets the temperature control design flow of the energy storage inverter, and a coolant flow suitable for single PCS cooling is generated; when the liquid cooling control instruction is a single battery cooling mode, the water pump of the water cooling unit is adjusted to an operating speed that meets the temperature control design flow of the battery pack, and a coolant flow suitable for single battery cooling is generated; when the liquid cooling control instruction is a dual-circuit cooling mode, the water pump of the water cooling unit is adjusted to an operating speed that meets the temperature control design flow of the energy storage inverter and the battery pack at the same time, and a coolant flow suitable for dual-circuit cooling is generated; when the liquid cooling control instruction is a fully closed mode, the operation of the water pump of the water cooling unit is stopped to generate zero coolant flow.

[0032] Optionally, when the liquid cooling control instruction is single PCS cooling mode, it means that cooling resources need to be concentrated to reduce the temperature of the energy storage converter. In this mode, the water pump speed of the water cooling unit is adjusted to a specific level to ensure that enough coolant flow is generated to meet the temperature control design requirements of the PCS. Adjusting the water pump speed to the appropriate level can accurately control the amount of coolant flowing to the PCS to ensure that it does not affect performance or safety due to excessive temperature. Next, when the liquid cooling control instruction specifies single battery cooling mode, the focus of adjustment shifts to the battery pack. In this mode, the speed of the water pump is adjusted to generate sufficient and dedicated coolant flow to meet the temperature control requirements of the battery pack. This focused cooling helps protect the battery pack from overheating or overcooling, maintaining battery performance and extending its service life. When the liquid cooling control instruction is dual-circuit cooling mode, it means that both the energy storage converter and the battery pack need to be cooled. At this time, the speed of the water pump must be adjusted to a higher level to meet the temperature control design flow requirements of both components at the same time. Through this regulation, the coolant flow generated by the water pump is sufficient to cover two independent circuits, thereby effectively controlling the temperature of the two system components and ensuring the overall efficiency and stability of the system. Finally, when the liquid cooling control instruction is in full shutdown mode, it means that the current system conditions do not require additional cooling. In this case, the water pump of the water cooling unit will be stopped to prevent unnecessary energy consumption and reduce the operating cost of the system. This measure avoids the circulation of coolant because the temperatures of the PCS and battery pack are within a safe and ideal operating range in this mode. Through these steps to regulate the speed of the water pump, it is possible to ensure that the cooling needs in various operating modes are met, thereby achieving high efficiency and high performance operation of the system. This dynamic adjustment mechanism optimizes energy use, enhances the responsiveness of the system, and improves the reliability and safety of the entire energy storage system.

[0033] Furthermore, the coolant flow rate matching the current liquid cooling working mode is generated, including:

[0034] The coolant demand flow formula is introduced, and the coolant demand flow formula is expressed as: Among them, F is the required coolant flow, Q is the required heat for temperature control, C p is the heat capacity of the coolant, ΔT is the temperature difference; when the liquid cooling control instruction is a single PCS cooling mode, the coolant flow rate adapted to the single PCS cooling is calculated according to the coolant demand flow formula; when the liquid cooling control instruction is a single battery cooling mode, the coolant flow rate adapted to the single battery cooling is calculated according to the coolant demand flow formula; when the liquid cooling control instruction is a dual-circuit cooling mode, the corresponding coolant flow rate is calculated according to the temperature control demand heat level of the energy storage inverter and the battery pack, and the coolant flow rate adapted to the dual-circuit cooling is obtained by adding them.

[0035] Specifically, according to the real-time temperature control target, the cooling demand heat Q is determined by comparing the current temperature of the PCS and battery pack with the ideal operating temperature difference. For example, if the real-time temperature of the PCS is 10°C higher than its set optimal operating temperature, it is necessary to calculate the heat required to maintain or reach the ideal temperature under this temperature difference. Then, through the known specific heat capacity C p And the calculated temperature difference ΔT can be used using the formula The required coolant flow F is calculated. This calculation ensures that the cooling system can provide sufficient coolant flow to effectively control the temperature of the PCS and battery pack to prevent overheating or performance degradation under low temperatures. In addition, the application of this calculation method is not limited to a single device. In dual-circuit refrigeration mode, for example, when the PCS and battery pack need to be cooled at the same time, this method can calculate the required coolant flow for each device separately and add the two flows to provide the appropriate total coolant volume for the entire system. Finally, through this precise coolant demand calculation, the energy management system can control the operation of the water pump more effectively, ensuring that the appropriate amount of cooling is provided to each part of the energy storage system without wasting resources, thereby optimizing the energy efficiency and performance of the entire system. This systematic approach improves energy utilization efficiency while also extending the service life of equipment and reducing maintenance costs.

[0036] Furthermore, based on the coolant flow rate, the coolant is distributed to the energy storage converter circuit and the battery pack circuit by adjusting the opening and closing angle of the three-way valve to form an initial liquid cooling path, including:

[0037] When the liquid cooling working mode is the single PCS cooling mode, the opening and closing angles of the three-way valve are set to the state of fully opening the energy storage inverter circuit and fully closing the battery pack circuit to form an initial liquid cooling path for single PCS cooling; when the liquid cooling working mode is the single battery cooling mode, the opening and closing angles of the three-way valve are set to the state of fully opening the battery pack circuit and fully closing the energy storage inverter circuit to form an initial liquid cooling path for single battery cooling; when the liquid cooling working mode is the dual-circuit cooling mode, the opening and closing angles of the three-way valve are adjusted according to the coolant flow ratio of the energy storage inverter and the battery pack to form an initial liquid cooling path for dual-circuit cooling; when the liquid cooling working mode is the fully closed mode, the opening and closing angles of the three-way valve are set to the fully closed state to form an initial liquid cooling path for the fully closed mode.

[0038] Furthermore, when the liquid cooling system is in single PCS cooling mode, it means that only the energy storage converter needs to be cooled. In this mode, the opening and closing angle of the three-way valve is set to fully open the energy storage converter circuit and fully close the battery pack circuit. This setting ensures that all coolant output from the water cooling unit flows directly to the energy storage converter, and no coolant flows to the battery pack, thereby concentrating cooling resources to effectively reduce the temperature of the PCS and prevent it from overheating. Next, when the liquid cooling system is set to single battery cooling mode, the operation is reversed, and the three-way valve is adjusted to fully open the battery pack circuit and fully close the energy storage converter circuit. This ensures that the coolant flows completely to the battery pack, not the energy storage converter, thereby providing focused cooling to maintain the optimal temperature of the battery and ensure battery performance and life. In dual-circuit cooling mode, both the energy storage converter and the battery pack need to be cooled. At this time, the opening and closing angle of the three-way valve is precisely adjusted according to the ratio of the coolant flow of the two. This adjustment is based on the previously calculated coolant demand to ensure that the coolant can be evenly distributed to the PCS and the battery pack to meet the thermal management needs of both. This flexible regulation allows the system to maintain stable operation of all key components under high load conditions. Finally, when the liquid cooling system is in full shutdown mode, the three-way valve is set to a fully closed state. This usually occurs when the temperature of the energy storage system fully meets the operating standards and no additional cooling is required. The full shutdown mode can effectively save energy, reduce operating costs, and reduce wear and tear on the system. Through these steps, not only the thermal management efficiency and reliability of the energy storage system are improved, but also the energy consumption and system performance are optimized by precisely controlling the flow of coolant. This control method ensures that the energy storage system can operate efficiently and safely under various operating conditions.

[0039] Furthermore, by establishing a real-time twin model, a cooling simulation is performed based on the initial liquid cooling path, the coolant flow is optimized according to the simulation results, and an optimized liquid cooling control scheme is generated, including:

[0040] A real-time twin model is established to simulate the coolant flow, heat exchange and temperature change process in the energy storage system to obtain a virtual model of the liquid cooling system of the energy storage system; based on the real-time data and the initial liquid cooling path, the current temperature data of the energy storage inverter and the battery pack are input into the real-time twin model for cooling simulation to obtain a cooling simulation result; according to the cooling simulation result, it is determined whether the temperature of the energy storage inverter and the battery pack can be reduced to a preset temperature threshold within the specified time, and whether the predetermined temperature control target is met; if not, the coolant flow rate is adjusted, and simulation is performed according to the adjustment result until the coolant flow rate that meets the predetermined temperature control target is obtained, and an optimized liquid cooling control scheme is generated according to the adjustment result; if satisfied, the initial liquid cooling path is output as the optimized liquid cooling control scheme.

[0041] Exemplarily, building a real-time twin model involves replicating the physical behavior and thermodynamic characteristics of the energy storage system on a digital platform. The model simulates the coolant flow, heat exchange process, and temperature changes inside the system in detail, providing a virtual operating environment for the system. Through this model, the performance of the system under different conditions can be predicted and analyzed without affecting the actual system operation. Next, based on the collected real-time data, such as the current temperature of the energy storage converter and the battery pack, these data are input into the real-time twin model. Using the initial liquid cooling path, that is, the liquid cooling route set according to the working mode, the model performs a cooling simulation. This simulation process can observe the cooling effect in actual operation, including whether the coolant is evenly distributed and its actual impact on the device temperature. The results of the simulation will be used to evaluate whether the temperature of the PCS and the battery pack can be adjusted to a preset temperature threshold within a set time. This evaluation standard is set according to the optimal operating temperature and safety standards of the equipment. If the simulation results show that the current coolant flow and distribution method cannot meet the temperature control target, the coolant flow needs to be adjusted. The adjustment process includes increasing or decreasing the amount of coolant flowing to a specific component, and then re-simulating to confirm whether the adjustment is effective. This iterative process continues until the simulation results show that the temperature can be stabilized within the preset threshold. Once this goal is achieved, an optimized liquid cooling control scheme is generated based on the adjusted final simulation results. If the initial simulation has shown that the existing liquid cooling path can effectively control the temperature, no further adjustment is required, and this path can be directly determined as the optimized liquid cooling control scheme. In this way, the system not only ensures operating efficiency, but also optimizes energy consumption, improving overall economy and safety. Through this simulation and optimization process, it is ensured that the key components of the energy storage system can be maintained in an ideal temperature range under various operating conditions, thereby improving the reliability, efficiency and life of the system.

[0042] Furthermore, if it is not satisfied, the coolant flow rate is adjusted, and simulation is performed according to the adjustment result until the coolant flow rate that meets the predetermined temperature control target is obtained, and an optimized liquid cooling control scheme is generated according to the adjustment result, including:

[0043] When the cooling simulation result does not meet the predetermined temperature control target, adjust the coolant flow rate, re-simulate through the real-time twin model, and obtain a first cooling simulation result; if the first cooling simulation does not meet the predetermined temperature control target, continue to adjust the coolant flow rate until the predetermined temperature control target is met, obtain the coolant flow rate that meets the temperature control target, and determine the optimized coolant flow rate; based on the optimized coolant flow rate, generate an optimized liquid cooling control scheme, including the adjusted coolant flow rate, water pump speed, and valve opening and closing angle.

[0044] Specifically, when the results of the initial simulation indicate that the current coolant flow fails to reduce the temperature of the energy storage converter (PCS) and the battery pack to the preset safe or optimal operating range, the system will start the coolant flow adjustment process. At this stage, depending on the specific differences in the simulation results, the adjustment involves increasing or decreasing the amount of coolant flowing to key components in an attempt to dissipate heat more effectively or avoid overcooling. After the adjustment, the cooling simulation is performed again through the real-time twin model. This simulation takes into account the new coolant flow setting and observes its impact on the component temperature. This simulation is called the first cooling simulation result. If the simulation results still fail to meet the temperature control target, the system will continue to adjust the coolant flow and repeat the simulation process. This iterative process continues until the simulation results confirm that the new coolant flow can stably maintain the temperature of the PCS and the battery pack within the predetermined threshold. Once the coolant flow that meets the predetermined temperature control target is reached, the system fixes this flow as the optimal setting and generates an optimized liquid cooling control solution based on it. This optimization scheme includes not only the adjusted coolant flow rate, but also the corresponding water pump speed and the opening and closing angle of the three-way valve. The precise adjustment of these parameters ensures the efficient operation of the entire system, optimizes energy consumption, and improves the safety and reliability of system operation. In addition, the optimized liquid cooling control scheme generated in this process will be used as a standard setting in future operations to cope with similar thermal load conditions. This systematic approach not only improves the response efficiency of the energy storage system, but also enhances the system's adaptability to changing operating conditions through real-time monitoring and adaptive adjustment.

[0045] Through the technical solutions of the above embodiments, the liquid cooling partition intelligent control method for an energy storage system provided in this application has the following technical effects:

[0046] 1. By installing temperature sensors for the PCS and battery pack respectively, their operating temperatures are monitored in real time. These data are fed into the energy management system (EMS) for analyzing the current heat demand, so that the system has an accurate understanding of the thermal conditions of each component, thereby providing more refined control and ensuring that each part can operate within the optimal temperature range, thereby improving overall efficiency and equipment life.

[0047] 2. Based on real-time temperature data and analysis results, EMS selects the most suitable liquid cooling working mode, such as single PCS cooling, single battery cooling, dual-circuit cooling or full shutdown mode, and generates corresponding liquid cooling control instructions. This strategy allows the system to flexibly respond to different thermal management requirements and only run the liquid cooling system in the necessary parts, significantly reducing unnecessary energy consumption while maintaining system stability and efficiency.

[0048] 3. Adjust the opening and closing state of the three-way valve according to the selected liquid cooling mode, optimize the flow and distribution of the coolant, and achieve different cooling needs by adjusting the running speed of the water pump and the angle of the valve to ensure that the coolant can be accurately distributed to the PCS or battery pack, or both, as needed, so as to achieve the highest heat exchange efficiency and energy saving effect.

[0049] 4. Establish a real-time twin model to simulate the cooling process, and adjust the coolant flow rate based on the simulation results to optimize the overall cooling effect. Through simulation and optimization, it can ensure that each liquid cooling decision is based on the most accurate data and predictive models, further improve the flexibility of system response and cooling efficiency, and ensure that the system can achieve the ideal temperature control standard under any operating conditions.

[0050] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0051] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0052] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A liquid cooling partition intelligent control method for an energy storage system, characterized in that: include: Acquire real-time operation data of the energy storage system, including temperature data of the energy storage converter and the battery pack, wherein the temperature data of the energy storage converter is collected by the converter temperature sensor, and the temperature data of the battery pack is collected by the battery temperature sensor; Analyze the current heat demand of the energy storage system based on the energy storage converter temperature data and the battery pack temperature data, and determine the real-time temperature control target; According to the real-time temperature control target, a liquid cooling working mode is selected through the energy management system, and the liquid cooling working mode includes a single PCS cooling mode, a single battery cooling mode, a dual-circuit cooling mode and a full-off mode, and a corresponding liquid cooling control instruction is generated; According to the liquid cooling control instruction, the operating speed of the water pump of the water cooling unit is adjusted to generate a coolant flow matching the current liquid cooling working mode; Based on the coolant flow rate, the coolant is distributed to the energy storage converter circuit and the battery pack circuit by adjusting the opening and closing angle of the three-way valve to form an initial liquid cooling path; By establishing a real-time twin model, a cooling simulation is performed based on the initial liquid cooling path, the coolant flow is optimized according to the simulation results, and an optimized liquid cooling control scheme is generated; Liquid cooling control is performed according to the optimized liquid cooling control scheme.

2. A liquid cooling partition intelligent control method for an energy storage system according to claim 1, characterized in that: Based on the energy storage converter temperature data and the battery pack temperature data, the current heat demand of the energy storage system is analyzed to determine the real-time temperature control target, including: Comparing the temperature data of the energy storage converter with a preset temperature control range, and determining the heat demand of the energy storage converter according to the comparison result; Comparing the battery pack temperature data with the battery safety temperature range, and determining the heat demand of the battery pack according to the comparison result; Based on the heat demand of the energy storage inverter and the heat demand of the battery pack, real-time temperature control targets of the energy storage inverter and the battery pack are determined respectively.

3. The liquid cooling partition intelligent control method for energy storage system according to claim 1, characterized in that: According to the real-time temperature control target, the energy management system selects a liquid cooling working mode, which includes a single PCS cooling mode, a single battery cooling mode, a dual-circuit cooling mode and a full-off mode, and generates corresponding liquid cooling control instructions, including: When the real-time temperature control target only needs to control the temperature of the energy storage converter, the single PCS cooling mode is selected to generate a liquid cooling control instruction to open the PCS loop valve and close the battery loop valve; When the real-time temperature control target only needs to control the temperature of the battery pack, the single battery cooling mode is selected to generate a liquid cooling control instruction to open the battery circuit valve and close the PCS circuit valve; When the real-time temperature control target requires temperature control of both the energy storage converter and the battery pack, a dual-circuit cooling mode is selected to generate a liquid cooling control instruction for simultaneously opening the PCS circuit valve and the battery circuit valve; When the real-time temperature control target does not require temperature control, the full-close mode is selected to generate a liquid cooling control instruction to close all valves.

4. The liquid cooling partition intelligent control method for energy storage system according to claim 1, characterized in that: According to the liquid cooling control instruction, the running speed of the water pump of the water cooling unit is adjusted to generate a coolant flow matching the current liquid cooling working mode, including: When the liquid cooling control instruction is a single PCS cooling mode, the water pump of the water cooling unit is adjusted to an operating speed that meets the temperature control design flow of the energy storage converter, and a coolant flow adapted to single PCS cooling is generated; When the liquid cooling control instruction is a single battery cooling mode, the water pump of the water cooling unit is adjusted to an operating speed that meets the battery pack temperature control design flow rate, and a coolant flow rate adapted to single battery cooling is generated; When the liquid cooling control instruction is a dual-circuit cooling mode, the water pump of the water cooling unit is adjusted to an operating speed that simultaneously meets the temperature control design flow of the energy storage converter and the battery pack, and a coolant flow adapted to the dual-circuit cooling is generated; When the liquid cooling control instruction is in the full-close mode, the operation of the water pump of the water cooling unit is stopped to generate zero coolant flow.

5. A liquid cooling partition intelligent control method for an energy storage system according to claim 4, characterized in that: Generates coolant flow that matches the current liquid cooling operating mode, including: The coolant demand flow formula is introduced, and the coolant demand flow formula is expressed as: Among them, F is the required coolant flow, Q is the required heat for temperature control, C p is the heat capacity of the coolant, ΔT is the temperature difference; When the liquid cooling control instruction is a single PCS cooling mode, the coolant flow rate adapted to the single PCS cooling is calculated according to the coolant demand flow rate formula; When the liquid cooling control instruction is a single battery cooling mode, the coolant flow rate adapted to the single battery cooling is calculated according to the coolant demand flow rate formula; When the liquid cooling control instruction is a dual-circuit cooling mode, the corresponding coolant flow rates are calculated based on the temperature control requirements of the energy storage inverter and the battery pack, and the coolant flow rates adapted to the dual-circuit cooling are added together.

6. The liquid cooling partition intelligent control method for energy storage system according to claim 1, characterized in that: Based on the coolant flow rate, the coolant is distributed to the energy storage converter circuit and the battery pack circuit by adjusting the opening and closing angle of the three-way valve to form an initial liquid cooling path, including: When the liquid cooling working mode is the single PCS cooling mode, the opening and closing angles of the three-way valve are set to fully open the energy storage converter circuit and fully close the battery pack circuit to form an initial liquid cooling path for single PCS cooling; When the liquid cooling working mode is the single battery cooling mode, the opening and closing angles of the three-way valve are set to fully open the battery pack circuit and fully close the energy storage converter circuit to form an initial liquid cooling path for single battery cooling; When the liquid cooling working mode is the dual-circuit cooling mode, the opening and closing angles of the three-way valve are adjusted according to the coolant flow ratio of the energy storage converter and the battery pack to form an initial liquid cooling path for dual-circuit cooling; When the liquid cooling working mode is the fully closed mode, the opening and closing angle of the three-way valve is set to a fully closed state to form an initial liquid cooling path of the fully closed mode.

7. The liquid cooling partition intelligent control method for energy storage system according to claim 1, characterized in that: By establishing a real-time twin model, a cooling simulation is performed based on the initial liquid cooling path, the coolant flow is optimized according to the simulation results, and an optimized liquid cooling control scheme is generated, including: Establish a real-time twin model to simulate the coolant flow, heat exchange and temperature change process in the energy storage system, and obtain a virtual model of the liquid cooling system of the energy storage system; Based on the real-time data and the initial liquid cooling path, the current temperature data of the energy storage converter and the battery pack are input into the real-time twin model for cooling simulation to obtain a cooling simulation result; According to the cooling simulation results, determining whether the temperature of the energy storage converter and the battery pack can be reduced to a preset temperature threshold within a specified time, and determining whether a predetermined temperature control target is met; If not, adjust the coolant flow rate, and perform simulation based on the adjustment results until the coolant flow rate that meets the predetermined temperature control target is obtained, and generate an optimized liquid cooling control plan based on the adjustment results; If satisfied, the initial liquid cooling path is output as the optimized liquid cooling control solution.

8. The liquid cooling partition intelligent control method for energy storage system according to claim 1, characterized in that: If not, adjust the coolant flow rate and perform simulation based on the adjustment results until the coolant flow rate that meets the predetermined temperature control target is obtained. Generate an optimized liquid cooling control plan based on the adjustment results, including: When the cooling simulation result does not meet the predetermined temperature control target, adjusting the coolant flow rate, re-simulating through the real-time twin model, and obtaining a first cooling simulation result; If the first cooling simulation does not meet the predetermined temperature control target, continue to adjust the coolant flow until the predetermined temperature control target is met, obtain the coolant flow that meets the temperature control target, and determine the optimized coolant flow; According to the optimized coolant flow, an optimized liquid cooling control scheme is generated, including the adjusted coolant flow, water pump speed, and valve opening and closing angle.

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