Constant temperature control method for battery cell of energy storage system

Abstract

The invention discloses an energy storage system cell constant temperature control method, and the method comprises the steps: carrying out the charging and discharging circulation of different multiplying powers on a battery cluster of a cell through a charging and discharging device, adjusting the liquid outlet temperature of a liquid cooling unit, enabling the temperature of the cell to be maintained at different temperature target values, and obtaining an MAPCTT diagram; inputting the MAPCTT diagram into a neural network model, generating a temperature control curve of the liquid cooling unit, optimizing the temperature control curve of the liquid cooling unit by using a battery cluster charging and discharging efficiency array MAPeta and a liquid cooling unit power consumption array MAPS, and generating an energy storage cell constant temperature control model; and optimizing control parameters of the energy storage cell constant temperature control model, and optimizing the energy storage cell constant temperature control model to obtain an optimal constant temperature control curve. According to the invention, the constant temperature control requirements of the energy storage system cell operating under different charging and discharging rate working conditions in the charging and discharging process can be met; the purposes of stable operating temperature range of the battery cell, accurate regulation and control, guarantee of the highest operating efficiency of the battery and realization of more cycle times of the battery cluster are achieved.

Description

Technical Field

[0001] The present invention relates to the field of energy storage technology, and in particular to a method for controlling the constant temperature of a battery cell of an energy storage system. Background Art

[0002] In energy storage systems, battery cell temperature control is a key factor in ensuring battery performance, safety and life. Battery cells generate heat during the charging and discharging process. If the temperature is too high or uneven, it may cause battery performance degradation, shortened life and even safety accidents.

[0003] Traditional battery cell temperature control methods usually rely on simple PID control or fixed temperature control strategies. These methods often find it difficult to achieve precise temperature control when faced with complex operating conditions. This not only leads to a decline in battery performance and shortened life, but also increases safety risks. Summary of the invention

[0004] Based on this, the present invention provides a constant temperature control method for battery cells of an energy storage system to solve the problem that traditional battery cell temperature control methods are difficult to achieve accurate temperature control.

[0005] The present invention provides a method for controlling the constant temperature of a battery cell of an energy storage system, comprising:

[0006] Use charging and discharging equipment to perform charge and discharge cycles of different rates on the battery cluster of the battery cell, and adjust the liquid outlet temperature of the liquid cooling unit to keep the battery cell temperature at different temperature target values ​​to obtain MAP CTT picture;

[0007] The MAP CTT The graph is input into the neural network model to generate the temperature control curve of the liquid cooling unit, and the battery cluster charging and discharging efficiency array MAP is used η and liquid cooling unit power consumption array MAP S Optimizing the temperature control curve of the liquid cooling unit to generate a constant temperature control model for the energy storage cell;

[0008] Optimize the control parameters of the energy storage battery cell constant temperature control model, and optimize the energy storage battery cell constant temperature control model to obtain the optimal constant temperature control curve.

[0009] Before subjecting the battery cluster to charge and discharge cycles at different rates, the battery cells, battery packs, liquid cooling pipes and liquid cooling units are selected, and the different charge and discharge rate intervals and battery temperature target value intervals of the battery cells are determined.

[0010] Battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S The acquisition includes,

[0011] The battery cluster charge and discharge efficiency array MAP is obtained by monitoring the battery cluster charge and discharge efficiency and the power consumption of the liquid cooling unit. η and liquid cooling unit power consumption array MAP S .

[0012] The generation of the temperature control curve of the liquid cooling unit includes:

[0013] The refrigeration and heating capacity of the liquid cooling unit is used as the slope of the temperature control curve of the variable temperature control to generate a temperature control curve, and the temperature control curve is forward optimized through a neural network model to obtain the temperature control curve of the liquid cooling unit.

[0014] The operation of optimizing the constant temperature control model of the energy storage battery cell includes:

[0015] Through data training of charge and discharge cycles with different charge and discharge rates and different battery cell control target values, the model control parameters are continuously optimized so that the battery cell constant temperature control model of the energy storage system can achieve a battery cell operating temperature within the target value ±1.5℃ range;

[0016] Substitute the charge / discharge rate C and the target value of the battery core temperature T into the temperature control curve of the liquid cooling unit to obtain the real-time target value of the outlet temperature of the liquid cooling unit T x ′ y ;

[0017] The target cell temperature T and the actual cell control temperature T ′ For comparison, when |TT ′ |>1.5℃, the corresponding target value of the liquid outlet temperature of the liquid cooling unit is T x ′ y Failure to meet control requirements;

[0018] The energy storage cell constant temperature control model will not meet the control requirements of the liquid cooling unit outlet temperature target value T x ′ y And the corresponding battery cell temperature target value T, charge and discharge rate C value are returned to MAP CTT Figure, in Supplementary MAP CTT At the same time, the neural network model is used to control the target value of the liquid outlet temperature of the liquid cooling unit. xy =f(C, T) is continuously optimized and repeated 3-5 times to optimize the temperature control curve of the liquid cooling unit to meet the temperature control requirements of the battery cell operation.

[0019] The target value control curve function T of the liquid cooling unit outlet temperature xy The calculation includes,

[0020] T xy =F(C,R i ,k,Cp ,S,v,ρ,T 回 )=C 2* R i / (k*C p *S*v*ρ)+T 回 ;

[0021] C=P / U / C 额 ;

[0022] Among them, T xy represents the target value of the liquid outlet temperature of the liquid cooling unit, P represents the DC side charging and discharging power of the energy storage system, U represents the total voltage of the battery cluster, C 额 Indicates the current value corresponding to the rated charge and discharge rate of the battery cell, C indicates the system charge and discharge rate under power P, R i represents the equivalent DC internal resistance of the battery cluster, k represents the thermal conductivity of the energy storage system PACK, C p represents the specific heat capacity of the coolant, S represents the cross-sectional area of ​​the liquid cooling plate flow channel, v represents the coolant flow rate, ρ represents the coolant density, T 回 Indicates the real-time value of the return liquid temperature of the liquid cooling unit.

[0023] The acquisition of the optimal constant temperature control curve includes:

[0024] In the control curve function T of the target value of the outlet temperature of the liquid cooling unit xy = f(C, T) optimization, while optimizing the battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S Update and supplement, wait for the liquid cooling unit outlet temperature target value control curve function T xy =f(C,T) After meeting the battery cell operating temperature control requirements, add the battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S As the basic correction option, take the battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S The intersection point of the charge and discharge rate C and the target value of the battery cell temperature T is used as the optimal operating condition result output by the constant temperature control model of the energy storage battery cell and output to the EMS, finally achieving the optimal constant temperature control curve.

[0025] The MAP CTT The picture shows an array of charge and discharge rate-battery cell temperature-liquid cooling unit outlet temperature.

[0026] Beneficial effect: The present invention generates a cell temperature control curve by combining a constant temperature control model with a neural network model through multiple arrays of charge and discharge rate, liquid cooling unit water outlet temperature, cell temperature, liquid cooling unit power consumption and DC side system efficiency, so as to meet the constant temperature control requirements of the energy storage system cell under different charge and discharge rate conditions during the charge and discharge process, so as to achieve a stable cell operating temperature range and precise regulation, while ensuring the maximum operating efficiency of the battery and achieving more cycles for the battery cluster.

[0027] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings are used to better understand the present invention and do not constitute a limitation of the present invention.

[0029] Figure 1 is a schematic diagram of a process provided according to the present invention;

[0030] Figure 2 is a flow chart for generating a target value of the outlet liquid temperature of a liquid cooling unit according to the present invention;

[0031] Figure 3 is a topological diagram of a neural network model proposed according to the present invention;

[0032] Figure 4 It is a communication topology diagram of a constant temperature control system proposed in the present invention;

[0033] Figure 5 It is the temperature change curve of the battery cell under the indirect temperature control method;

[0034] Figure 6 It is the temperature change curve of the battery cell under the constant temperature control method proposed by the present invention. DETAILED DESCRIPTION

[0035] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0036] like Figure 1 As shown, the present invention provides a method for controlling the constant temperature of a battery cell of an energy storage system, comprising:

[0037] S1: Use the charging and discharging equipment to perform charge and discharge cycles of the battery cluster at different rates, and adjust the liquid outlet temperature of the liquid cooling unit to keep the battery temperature at different temperature target values ​​to obtain MAP CTT Figure. It should be noted that:

[0038] Before subjecting the battery cluster to charge and discharge cycles at different rates, the battery cells, battery packs, liquid cooling pipes and liquid cooling units are selected, and the different charge and discharge rate intervals and battery temperature target value intervals of the battery cells are determined.

[0039] The battery cells, battery packs, liquid cooling pipes and liquid cooling units are selected and confirmed to ensure the certainty of some parameters of the constant temperature control method of the battery cells of the energy storage system, such as the internal resistance of the battery cells, the heat exchange capacity between the cooling system and the battery cells, and the cooling capacity of the liquid cooling unit.

[0040] The battery pack is insulated, and the equipment or materials used can have the same insulation capacity as the energy storage outdoor cabinet, reducing the impact of ambient temperature on the temperature of the battery cell.

[0041] The present invention selects 10% of 0.5C of the battery cell as the rate interval point and selects 5°C as the temperature interval point, taking into account the control method's demand for data volume and control of time cost.

[0042] The MAP CTT The picture shows an array of charge and discharge rate-battery cell temperature-liquid cooling unit outlet temperature.

[0043] MAP CTT Drawing of the graph includes:

[0044] Adjust the charge and discharge rate to C1, and adjust the outlet temperature of the liquid cooling unit to T 11 , T 12 , T 13 ,……,T 1n , so that the battery cell temperature is controlled at T1, T2, T3, ..., T n ;

[0045] Adjust the charge and discharge rate to C2, and adjust the liquid outlet temperature of the liquid cooling unit to T 21 , T 22 , T 23 ,……,T 2n , so that the battery cell temperature is controlled at T1, T2, T3, ..., T n ;

[0046] Adjust the charge and discharge rate to C3, and adjust the outlet temperature of the liquid cooling unit to T 31 , T 32 , T 33 ,……,T 3n , so that the battery cell temperature is controlled at T1, T2, T3, ..., Tn ;

[0047] Adjust the charge and discharge rate to C n , adjust the outlet temperature of the liquid cooling unit to T n1 , T n2 , T n3 ,……,T nn , so that the battery cell temperature is controlled at T1, T2, T3, ..., T n ;

[0048] At the same time, the DC side system efficiency η and the power consumption S of the liquid cooling unit are recorded simultaneously during the 30-min stabilization period of temperature control.

[0049] MAP is drawn by the above method CTT picture.

[0050] S2: The MAP CTT The graph is input into the neural network model to generate the temperature control curve of the liquid cooling unit, and the battery cluster charging and discharging efficiency array MAP is used η and liquid cooling unit power consumption array MAP S The temperature control curve of the liquid cooling unit is optimized to generate a constant temperature control model for the energy storage cell.

[0051] Battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S The acquisition includes,

[0052] The battery cluster charge and discharge efficiency array MAP is obtained by monitoring the battery cluster charge and discharge efficiency and the power consumption of the liquid cooling unit. η and liquid cooling unit power consumption array MAP S .

[0053] The generation of the temperature control curve of the liquid cooling unit includes:

[0054] The refrigeration and heating capacity of the liquid cooling unit is used as the slope of the temperature control curve of the variable temperature control to generate a temperature control curve, and the temperature control curve is forward optimized through a neural network model to obtain the temperature control curve of the liquid cooling unit.

[0055] S3: Optimizing the control parameters of the energy storage cell constant temperature control model, and optimizing the energy storage cell constant temperature control model to obtain an optimal constant temperature control curve. It should be noted that:

[0056] By optimizing the control parameters, the system operating conditions of the battery cells, PACK, liquid cooling pipes, liquid cooling units and other equipment in the cold plate liquid cooling system can be fitted, so that the energy storage battery cell constant temperature control model is suitable for different liquid cooling systems. The constant battery cell temperature control method is used to obtain the corresponding battery cell temperature control curve to achieve the purpose of battery cell temperature control requirements.

[0057] The operation of optimizing the constant temperature control model of the energy storage battery cell includes:

[0058] Through data training of charge and discharge cycles with different charge and discharge rates and different battery cell control target values, the model control parameters are continuously optimized so that the battery cell constant temperature control model of the energy storage system can achieve a battery cell operating temperature within the target value ±1.5℃ range;

[0059] Substitute the charge / discharge rate C and the target value of the battery core temperature T into the temperature control curve of the liquid cooling unit to obtain the real-time target value of the outlet temperature of the liquid cooling unit T x ′ y ;

[0060] The target cell temperature T and the actual cell control temperature T ′ For comparison, when |TT ′ |>1.5℃, the corresponding target value of the liquid outlet temperature of the liquid cooling unit is T x ′ y Failure to meet control requirements;

[0061] The energy storage cell constant temperature control model will not meet the control requirements of the liquid cooling unit outlet temperature target value T x ′ y And the corresponding battery cell temperature target value T, charge and discharge rate C value are returned to MAP CTT Figure, in Supplementary MAP CTT At the same time, the neural network model is used to control the target value of the liquid outlet temperature of the liquid cooling unit. xy = f(C, T) for continuous optimization, repeat 3-5 times, optimize the temperature control curve of the liquid cooling unit, and meet the battery core operating temperature control requirements. The flow chart for generating the target value of the liquid outlet temperature of the liquid cooling unit is as follows: Figure 2 shown.

[0062] The target value control curve function T of the liquid cooling unit outlet temperature xy The calculation includes,

[0063] T xy =F(C,R i ,k,C p ,S,v,ρ,T 回 )=C 2* R i / (k*C p *S*v*ρ)+T 回 ;

[0064] C=P / U / C 额 ;

[0065] Among them, Txy represents the target value of the liquid outlet temperature of the liquid cooling unit, P represents the DC side charging and discharging power of the energy storage system, U represents the total voltage of the battery cluster, C 额 Indicates the current value corresponding to the rated charge and discharge rate of the battery cell, C indicates the system charge and discharge rate under power P, R i represents the equivalent DC internal resistance of the battery cluster, k represents the thermal conductivity of the energy storage system PACK, C p represents the specific heat capacity of the coolant, S represents the cross-sectional area of ​​the liquid cooling plate flow channel, v represents the coolant flow rate, ρ represents the coolant density, T 回 Indicates the real-time value of the return liquid temperature of the liquid cooling unit.

[0066] T xy With T 回 The difference is constrained within 1°C to ensure that the temperature extremes of the cells in a single PACK of the battery cluster are minimized.

[0067] The acquisition of the optimal constant temperature control curve includes:

[0068] In the control curve function T of the target value of the outlet temperature of the liquid cooling unit xy = f(C, T) optimization, while optimizing the battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S Update and supplement, wait for the liquid cooling unit outlet temperature target value control curve function T xy =f(C,T) After meeting the battery cell operating temperature control requirements, add the battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S As the basic correction option, take the battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S The intersection point of the charge and discharge rate C and the target value of the battery cell temperature T is used as the optimal operating condition result output by the constant temperature control model of the energy storage battery cell and output to the EMS, finally achieving the optimal constant temperature control curve.

[0069] The neural network model topology is as follows Figure 3 As shown in the figure, the neural network model can calculate the charge and discharge rate C, the cell internal resistance R i , the circulating fluid flow rate v and other parameters are adjusted, and the return liquid temperature T 回 Real-time data collection is performed, and the target value T of the liquid cooling unit output that meets the temperature control requirements is generated. xy The temperature control curve of C and T, where the actual value of the liquid outlet temperature of the liquid cooling unit tracks the target value T xy The timeliness is guaranteed by the variable frequency compressor controlled by the PID of the liquid cooling unit. At the same time, the number of neurons in the neural network model can be increased according to the EMS hardware carrying capacity to speed up the optimization rate of the temperature control curve.

[0070] In order to realize the constant temperature control method of the battery cell of the energy storage system, a 100kW / 232kWh tower liquid cooling outdoor cabinet is selected to perform the MAP of the charge and discharge rate-battery cell temperature-liquid cooling unit outlet temperature. CTT Figure 3. Data collection and verification of the control effect of the constant temperature control algorithm of the battery cell of the energy storage system.

[0071] The conventional energy storage system DC side solution is composed of 5 1P52S battery PACKs (battery packs) connected in series, equipped with a high-voltage box and a BMS (Battery Management System). The BMS system provides the temperature control host with the temperature of the single cell, the average temperature and the extreme temperature (the communication topology diagram of the constant temperature control system is shown in the figure). Figure 4 As shown). The battery PACK is installed in the battery compartment. The battery compartment uses 50mm thick insulation and fireproof rock wool. The protection level of the battery compartment is IP65, ensuring that the heat exchange between the battery compartment and the outside of the compartment has little effect on the temperature change of the battery cell and can be ignored. The energy storage system is equipped with a liquid cooling unit, which uses PID algorithm control and frequency conversion tracking technology to control the outlet liquid temperature. When the ambient temperature is 45℃ and the outlet water temperature is 18℃, the water flow rate is 46L / min (ensuring that the inlet and outlet liquid temperature difference is less than 1℃), the cooling capacity is 5.088kW, the input power is 2.482kW, and the heating power is 2kW, which meets the requirement that the outlet liquid temperature of the liquid cooler is consistent with the target value in real time. The temperature control subsystem uses multi-stage variable diameter liquid cooling pipes to avoid the inconsistency of the coolant flow of each PACK due to the height of the PACK installation position, resulting in a large temperature difference between the cells of each PACK in the battery cluster, thereby reducing the interference of the difference in the average temperature of each PACK cell to the constant temperature control method of the energy storage system cell to negligible. The constant temperature control model of the energy storage system battery cell runs in the EMS (Energy Management System). The battery cell temperature data is collected through communication between EMS and BMS, and the liquid outlet and return temperatures of the liquid cooling unit are collected through communication between EMS and the liquid cooling unit. The liquid outlet temperature target value is issued, forming a millisecond-level data flow loop for the constant temperature control method of the energy storage system battery cell. This communication architecture ensures the timeliness of the temperature control adjustment of the energy storage system.

[0072] Figure 5 is the temperature change curve of the battery cell under the indirect temperature control method. Figure 6 The temperature change curve of the battery cell under the constant temperature control method proposed in the present invention, where different colored lines represent the operating temperature curves of different battery cells. Figure 5 and Figure 6It can be seen that the constant temperature control method proposed in the present invention continuously optimizes the model control parameters through data training of charge and discharge cycles with different charge and discharge rates and different battery cell control target values, so that the energy storage system battery cell constant temperature control model can achieve the battery cell operating temperature within the target value ±1.5°C range, meet the energy storage system battery cell constant temperature control requirements under different charge and discharge rate conditions during the charge and discharge process, achieve the battery cell operating temperature range is stable, precise regulation, while ensuring the highest operating efficiency of the battery and achieving more cycles of the battery cluster.

[0073] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for controlling the constant temperature of a battery cell of an energy storage system, characterized in that: include: Use charging and discharging equipment to perform charge and discharge cycles of different rates on the battery cluster of the battery cell, and adjust the liquid outlet temperature of the liquid cooling unit to keep the battery cell temperature at different temperature target values ​​to obtain MAP CTT picture; The MAP CTT The graph is input into the neural network model to generate the temperature control curve of the liquid cooling unit, and the battery cluster charging and discharging efficiency array MAP is used η and liquid cooling unit power consumption array MAP S Optimizing the temperature control curve of the liquid cooling unit to generate a constant temperature control model for the energy storage cell; Optimize the control parameters of the energy storage battery cell constant temperature control model, and optimize the energy storage battery cell constant temperature control model to obtain the optimal constant temperature control curve.

2. A method for controlling the constant temperature of a battery cell of an energy storage system according to claim 1, characterized in that: Before subjecting the battery cluster to charge and discharge cycles at different rates, the battery cells, battery packs, liquid cooling pipes and liquid cooling units are selected, and the different charge and discharge rate intervals and battery temperature target value intervals of the battery cells are determined.

3. A method for controlling the constant temperature of a battery cell of an energy storage system according to claim 1 or 2, characterized in that: Battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S The acquisition includes, The battery cluster charge and discharge efficiency array MAP is obtained by monitoring the battery cluster charge and discharge efficiency and the power consumption of the liquid cooling unit. η and liquid cooling unit power consumption array MAP S .

4. A method for controlling the constant temperature of a battery cell of an energy storage system according to claim 3, characterized in that: The generation of the temperature control curve of the liquid cooling unit includes: The refrigeration and heating capacity of the liquid cooling unit is used as the slope of the temperature control curve of the variable temperature control to generate a temperature control curve, and the temperature control curve is forward optimized through a neural network model to obtain the temperature control curve of the liquid cooling unit.

5. A method for controlling the constant temperature of a battery cell of an energy storage system according to claim 4, characterized in that: The operation of optimizing the constant temperature control model of the energy storage battery cell includes: Through data training of charge and discharge cycles with different charge and discharge rates and different battery cell control target values, the model control parameters are continuously optimized so that the battery cell constant temperature control model of the energy storage system can achieve a battery cell operating temperature within the target value ±1.5℃ range; Substitute the charge / discharge rate C and the target value of the battery core temperature T into the temperature control curve of the liquid cooling unit to obtain the real-time target value of the outlet temperature of the liquid cooling unit T x ′ y ; The target cell temperature T and the actual cell control temperature T ′ For comparison, when |TT ′ |>1.5℃, the corresponding target value of the liquid outlet temperature of the liquid cooling unit is T x ′ y Failure to meet control requirements; The energy storage cell constant temperature control model will not meet the control requirements of the liquid cooling unit outlet temperature target value T x ′ y And the corresponding battery cell temperature target value T, charge and discharge rate C value are returned to MAP CTT Figure, in Supplementary MAP CTT At the same time, the neural network model is used to control the target value of the liquid outlet temperature of the liquid cooling unit. xy =f(C, T) is continuously optimized and repeated 3-5 times to optimize the temperature control curve of the liquid cooling unit to meet the temperature control requirements of the battery cell operation.

6. A method for controlling constant temperature of battery cells in an energy storage system according to claim 5, characterized in that: The target value control curve function T of the liquid cooling unit outlet temperature xy The calculation includes, T xy =F(C,R i ,k,C p ,S,v,ρ,T 回 )=C 2* R i / (k*C p *S*v*ρ)+T 回 ; C=P / U / C 额 ; Among them, T xy represents the target value of the liquid outlet temperature of the liquid cooling unit, P represents the DC side charging and discharging power of the energy storage system, U represents the total voltage of the battery cluster, C 额 Indicates the current value corresponding to the rated charge and discharge rate of the battery cell, C indicates the system charge and discharge rate under power P, R i represents the equivalent DC internal resistance of the battery cluster, k represents the thermal conductivity of the energy storage system PACK, C p represents the specific heat capacity of the coolant, S represents the cross-sectional area of ​​the liquid cooling plate flow channel, v represents the coolant flow rate, ρ represents the coolant density, T 回 Indicates the real-time value of the return liquid temperature of the liquid cooling unit.

7. A method for controlling constant temperature of battery cells in an energy storage system according to claim 6, characterized in that: The acquisition of the optimal constant temperature control curve includes: In the control curve function T of the target value of the outlet temperature of the liquid cooling unit xy = f(C, T) optimization, while optimizing the battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S Update and supplement, wait for the liquid cooling unit outlet temperature target value control curve function T xy =f(C,T) After meeting the battery cell operating temperature control requirements, add the battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S As the basic correction option, take the battery cluster charge and discharge efficiency array MAP η and liquid cooling unit power consumption array MAP S The intersection point of the charge and discharge rate C and the target value of the battery cell temperature T is used as the optimal operating condition result output by the constant temperature control model of the energy storage battery cell and output to the EMS, finally achieving the optimal constant temperature control curve.

8. The method for controlling the constant temperature of a battery cell of an energy storage system according to claim 1, characterized in that: The MAP CTT The picture shows an array of charge and discharge rate-battery cell temperature-liquid cooling unit outlet temperature.

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