Electrochemical energy storage liquid cooling unit control method, device and equipment and storage medium

Abstract

The invention relates to an electrochemical energy storage liquid cooling unit control method and device, equipment and a storage medium. The main technical scheme comprises the following steps: acquiring a temperature deviation value and a calorific value trend value of a cell system; according to the temperature deviation value, the calorific value trend value and a preset fuzzy control model, control parameters are obtained; obtaining a target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameters and a preset controller model; and a water outlet temperature value of the liquid cooling unit is obtained, and the operation gear of the liquid cooling unit is adjusted according to the target temperature value, the water outlet temperature value and a preset comparison threshold value. The target temperature value of the liquid cooling unit can be obtained based on the fuzzy control model and the controller model, the operation gear of the liquid cooling unit is adjusted based on the target temperature value of the liquid cooling unit and the temperature value of the water outlet, the stability of the temperature of the liquid cooling unit is controlled, the safety of the whole energy storage system is improved, and the energy storage efficiency is improved. And the service life of the whole energy storage system is prolonged.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage systems, and in particular to a control method, device, equipment and storage medium for an electrochemical energy storage liquid cooling unit. Background Art

[0002] The electrochemical energy storage system is a set of power system devices that use energy storage batteries for charging and discharging. It consists of a battery PACK, a battery cooling system, a BMS (Battery Management System) and other auxiliary systems. As we all know, the battery PACK is composed of many stacked batteries. The charging and discharging process of the energy storage system mainly refers to the charging and discharging process of the battery system. During the charging and discharging process of the battery system, the battery will release a lot of heat. If the battery is not cooled in time, the battery system will experience thermal runaway, which will cause the entire energy storage system to catch fire.

[0003] At present, due to the long cooling pipeline of the battery cooling system, i.e. the liquid cooling unit, and the uncertainty of the current new heat generation of the battery system; if the gear position of the liquid cooling unit and the cooling temperature of the coolant are not set properly, the energy storage system may be over-cooled or under-cooled. The temperature abnormality of the battery system will directly affect the charging and discharging efficiency of the entire energy storage system, and thus affect the overall revenue. Therefore, the current liquid cooling unit is set to accept the start / shutdown command of other systems (BMS). When the liquid cooling unit receives the shutdown command, the liquid cooling unit stops running; or the liquid cooling unit starts cooling after receiving the start command.

[0004] However, the above method performs cooling according to a preset target cooling temperature of the coolant and the operating gear of the liquid cooling unit, that is, the cooling operation is performed based on the pre-set operating logic of the liquid cooling unit. The cooling mechanism is relatively simple and cannot adjust the target parameters in time according to the current operating conditions of the energy storage system to improve the cooling efficiency. In other words, the heat generation trend of the battery cell system at present or in the short term in the future is not considered. The liquid cooling unit can only passively follow the result of the battery cell system heating up and operate passively, which leads to a large lag in the control operation of the liquid cooling unit and low timeliness. At the same time, due to the uncertainty of the future heat generation of the battery cell system, the cooling control effect of the liquid cooling unit is also very unstable. Summary of the invention

[0005] Based on this, the present application provides a control method, device, equipment and storage medium for an electrochemical energy storage liquid cooling unit, which can obtain the target temperature value of the liquid cooling unit based on a fuzzy control model and a controller model, and adjust the operating gear of the liquid cooling unit based on the target temperature value and the outlet temperature value of the liquid cooling unit to achieve control of the stability of the temperature of the liquid cooling unit, thereby achieving the effect of improving the safety of the overall energy storage system and extending the life of the overall energy storage system.

[0006] In a first aspect, a control method for an electrochemical energy storage liquid cooling unit is provided, the method comprising:

[0007] Obtain the temperature deviation value and the heating value trend value of the battery system. The temperature deviation value refers to the difference between the cooling target value of the liquid cooling unit and the actual temperature output value of the battery system.

[0008] According to the temperature deviation value, the heating value trend value and the preset fuzzy control model, the control parameters are obtained;

[0009] According to the temperature deviation value, the control parameter and the preset controller model, the target temperature value of the liquid cooling unit is obtained;

[0010] The water outlet temperature value of the liquid cooling unit is obtained, and the operating gear of the liquid cooling unit is adjusted according to the target temperature value, the water outlet temperature value and the preset comparison threshold.

[0011] According to an achievable method in an embodiment of the present application, obtaining a calorific value trend of a battery cell system includes:

[0012] Obtain charging and discharging instructions and rated operating power. The charging and discharging instructions are issued by the energy storage monitoring platform, and the rated operating power is set by the energy storage system;

[0013] According to the charge and discharge instructions, rated operating power and temperature deviation value, the heating value of the battery system is obtained.

[0014] According to an achievable method in the embodiment of the present application, the control parameters are obtained according to the temperature deviation value, the heating value trend value and the preset fuzzy control model, including:

[0015] The temperature deviation value and the calorific value trend value are divided into domains respectively, and the temperature deviation value domain and the calorific value trend value domain are obtained;

[0016] According to the temperature deviation value domain, the calorific value trend value domain and the membership functions corresponding to each domain, the temperature deviation membership parameter and the calorific value trend membership parameter are obtained;

[0017] The control parameters are obtained according to the temperature deviation membership parameter, the heating value trend membership parameter and the preset fuzzy control model.

[0018] According to an achievable method in an embodiment of the present application, the preset fuzzy control model includes a preset fuzzy rule table, and there are multiple control parameters; according to the temperature deviation membership parameter, the heating value trend membership parameter and the preset fuzzy control model, the control parameters are obtained, including:

[0019] Divide the domain of each control parameter to obtain the domain of each control parameter and the corresponding membership function;

[0020] According to the temperature deviation membership parameter, the heating value trend membership parameter, the preset fuzzy rule table, the control parameter domains and the corresponding membership functions, the membership values ​​and the individual values ​​of each membership function belonging to different control parameter domain intervals are obtained;

[0021] The corresponding control parameters are obtained according to the domain of each control parameter, the corresponding membership functions, the corresponding membership values, the corresponding numerical values ​​and the preset fuzzy formula.

[0022] According to an achievable method in an embodiment of the present application, a target temperature value of the liquid cooling unit is obtained according to the temperature deviation value, the control parameter and the preset controller model, including:

[0023] According to each control parameter and the control cycle of the liquid cooling unit, the control coefficient corresponding to each control parameter is obtained;

[0024] According to the temperature deviation value, each control coefficient, the control period and the preset controller model, the target temperature value of the liquid cooling unit is obtained.

[0025] According to an achievable method in an embodiment of the present application, the preset comparison threshold includes a first comparison threshold, and the operating gear of the liquid cooling unit is adjusted according to the target temperature value, the water outlet temperature value and the preset comparison threshold, including:

[0026] According to the target temperature value and the outlet temperature value, the temperature difference value is obtained;

[0027] Comparing the absolute value of the temperature difference with a first comparison threshold;

[0028] When the absolute value of the temperature difference is greater than or equal to the first comparison threshold, the operating gear of the liquid cooling unit is increased.

[0029] According to an achievable manner in the embodiment of the present application, the preset comparison threshold value further includes a second comparison threshold value, and the method further includes:

[0030] When the absolute value of the temperature difference is less than the first comparison threshold, the absolute value of the temperature difference is compared with the second comparison threshold;

[0031] When the absolute value of the temperature difference is less than the first comparison threshold but greater than or equal to the second comparison threshold, maintaining the current state of the liquid cooling unit;

[0032] When the absolute value of the temperature difference is less than the second comparison threshold, the operating gear of the liquid cooling unit is reduced.

[0033] In a second aspect, a control device for an electrochemical energy storage liquid cooling unit is provided, wherein the device comprises:

[0034] A first acquisition module is used to obtain a temperature deviation value and a heating value trend value of the battery system, wherein the temperature deviation value refers to the difference between a cooling target value of the liquid cooling unit and an actual temperature output value of the battery system;

[0035] A first calculation module is used to obtain control parameters according to the temperature deviation value, the heating value trend value and a preset fuzzy control model;

[0036] A second calculation module is used to obtain a target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameter and the preset controller model;

[0037] The output adjustment module is used to obtain the outlet temperature value of the liquid cooling unit and adjust the operating gear of the liquid cooling unit according to the target temperature value, the outlet temperature value and the preset comparison threshold.

[0038] In a third aspect, a computer device is provided, comprising:

[0039] at least one processor; and

[0040] a memory communicatively connected to at least one processor; wherein,

[0041] The memory stores computer instructions that can be executed by at least one processor, and the computer instructions are executed by at least one processor to enable the at least one processor to execute the method involved in the first aspect above.

[0042] In a fourth aspect, a computer-readable storage medium is provided, on which computer instructions are stored, characterized in that the computer instructions are used to enable a computer to execute the method involved in the above-mentioned first aspect.

[0043] According to the technical content provided in the embodiments of the present application, the temperature deviation value and the calorific value trend value of the battery system are obtained, and the temperature deviation value refers to the difference between the cooling target value of the liquid cooling unit and the actual temperature output value of the battery system; the control parameters are obtained according to the temperature deviation value, the calorific value trend value and the preset fuzzy control model; the target temperature value of the liquid cooling unit is obtained according to the temperature deviation value, the control parameters and the preset controller model; the outlet temperature value of the liquid cooling unit is obtained, and the operating gear of the liquid cooling unit is adjusted according to the target temperature value, the outlet temperature value and the preset comparison threshold. The present application can obtain the target temperature value of the liquid cooling unit based on the fuzzy control model and the controller model, and adjust the operating gear of the liquid cooling unit based on the target temperature value and the outlet temperature value of the liquid cooling unit, so as to control the stability of the temperature of the liquid cooling unit, thereby achieving the effect of improving the safety of the overall energy storage system and extending the life of the overall energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic flow chart of a control method for an electrochemical energy storage liquid cooling unit in one embodiment;

[0045] Figure 2 A membership function diagram of a temperature deviation value of a control method for an electrochemical energy storage liquid cooling unit in one embodiment;

[0046] Figure 3 A membership function diagram of a calorific value trend value of a control method for an electrochemical energy storage liquid cooling unit in one embodiment;

[0047] Figure 4 is a control parameter K of a control method for an electrochemical energy storage liquid cooling unit in an embodiment p Membership function diagram of ;

[0048] Figure 5 is a control parameter K of a control method for an electrochemical energy storage liquid cooling unit in an embodiment i Membership function diagram of ;

[0049] Figure 6 is a control parameter K of a control method for an electrochemical energy storage liquid cooling unit in an embodiment d Membership function diagram of ;

[0050] Figure 7 A schematic diagram of a preferred flow chart of a control method for an electrochemical energy storage liquid cooling unit in one embodiment;

[0051] Figure 8 is a structural block diagram of an electrochemical energy storage control device in one embodiment;

[0052] Fig. 9 FIG. 4 is a schematic structural diagram of a computer device in one embodiment. DETAILED DESCRIPTION

[0053] 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.

[0054] In one or more embodiments, the electrochemical energy storage liquid cooling unit control method provided in the present application can be applied to a computer device, which may include a terminal or a server. Specifically, the computer device can obtain a temperature deviation value and a calorific value trend value of the battery system, the temperature deviation value refers to the difference between the cooling target value of the liquid cooling unit and the actual temperature output value of the battery system; obtain control parameters according to the temperature deviation value, the calorific value trend value and the preset fuzzy control model; obtain the target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameters and the preset controller model; obtain the outlet temperature value of the liquid cooling unit, and adjust the operating gear of the liquid cooling unit according to the target temperature value, the outlet temperature value and the preset comparison threshold.

[0055] Figure 1 A flow chart of a control method for an electrochemical energy storage liquid cooling unit provided in an embodiment of the present application, such as Figure 1 As shown, the method may include the following steps:

[0056] Step S101: obtaining a temperature deviation value and a heating value trend value of a battery cell system.

[0057] Among them, the temperature deviation value refers to the difference between the cooling target value of the liquid cooling unit and the actual temperature output value of the battery system.

[0058] Here, there are two control objects available for the liquid cooling unit: the first is to adjust the cooling start temperature, cooling target temperature and cooling temperature of the liquid cooling unit; the second is to adjust the operating gear of the liquid cooling unit. Therefore, the cooling target value of the liquid cooling unit can be obtained, represented by r(t); the actual temperature output value of the battery system can be obtained, which can be represented by y(t); the difference between the cooling target value of the liquid cooling unit and the actual temperature output value of the battery system is calculated to obtain the temperature deviation value, which can be represented by e(t). Then the expression of e(t) can be expressed as follows:

[0059] e(t)=r(t)-y(t)

[0060] That is, e(t) represents the temperature deviation value at time t. By performing differential control on the temperature deviation value, the heating value trend of the battery system can be obtained, which is represented by ec(t), that is, the future heating trend of the battery system.

[0061] Step S103: obtaining control parameters according to the temperature deviation value, the heating value trend value and the preset fuzzy control model.

[0062] Here, due to the large time lag, nonlinear control effect, and strong multi-parameter coupling of the liquid cooling unit, it is impossible to establish a complete cooling control model for the liquid cooling unit and the battery system. Therefore, it is necessary to process it based on the fuzzy control model. The fuzzy control model can provide a very effective control strategy in dealing with uncertainty model systems, and has the advantages of strong robustness and strong anti-interference ability. The fuzzy control model adopts the form of two inputs and three outputs, that is, e(t) and ec(t) are input variables, K p , K i and K d The control parameter is the output variable, and the fuzzy control rules are used to achieve the control output of the control parameter.

[0063] Step S105: Obtaining a target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameters and the preset controller model.

[0064] Among them, the preset controller model can use PID controller, which is a linear controller with the advantages of simple structure and high reliability. PID control is a basic control method of control system in classical control theory. It is a linear regulator with proportional, integral and differential functions. It consists of proportional unit (P), integral unit (I) and differential unit (D). p , K i and K d The control is achieved by setting three parameters. Proportional control adjusts the control amount according to the size of the error, integral control adjusts the output according to the accumulated amount of the error, and differential control adjusts the output according to the error change rate. Therefore, the most critical issue is the formulation of the three parameters P, I, and D. After obtaining the control parameter K p , K i and K d After that, the target temperature value of the liquid cooling unit can be obtained based on the PID controller.

[0065] Step S107: obtaining the water outlet temperature value of the liquid cooling unit, and adjusting the operating gear of the liquid cooling unit according to the target temperature value, the water outlet temperature value and a preset comparison threshold.

[0066] Here, in the control process of the liquid cooling unit, it mainly includes the operating gear of the liquid cooling unit and the target temperature value of the coolant of the liquid cooling unit. Therefore, the operating gear of the liquid cooling unit can be adjusted based on the target temperature value and the outlet temperature value of the liquid cooling unit. And because the operating gear of the liquid cooling unit is mainly used to adjust the duty cycle of the air-conditioning refrigeration compressor, the higher the gear, the higher the duty cycle; the faster the coolant temperature drops; the lower the coolant refrigeration temperature, the more heat the coolant can take away after flowing through the battery system, the better the cooling effect, and the faster the cooling speed of the battery system, so by adjusting the operating gear of the liquid cooling unit, the temperature of the battery system can be further controlled.

[0067] It can be seen that the embodiment of the present application obtains the temperature deviation value and the calorific value trend value of the battery system, the temperature deviation value refers to the difference between the cooling target value of the liquid cooling unit and the actual temperature output value of the battery system; obtains the control parameter according to the temperature deviation value, the calorific value trend value and the preset fuzzy control model; obtains the target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameter and the preset controller model; obtains the outlet temperature value of the liquid cooling unit, and adjusts the operating gear of the liquid cooling unit according to the target temperature value, the outlet temperature value and the preset comparison threshold. The present application can obtain the target temperature value of the liquid cooling unit based on the fuzzy control model and the controller model, and adjust the operating gear of the liquid cooling unit based on the target temperature value and the outlet temperature value of the liquid cooling unit, so as to control the stability of the temperature of the liquid cooling unit, thereby achieving the effect of improving the safety of the overall energy storage system and extending the life of the overall energy storage system.

[0068] The following describes each step in the above method flow in detail. First, the "obtaining the calorific value trend of the battery cell system" in the above step 101 is described in detail in conjunction with the embodiment.

[0069] As a feasible method, the charge and discharge instructions and the rated operating power are obtained; according to the charge and discharge instructions, the rated operating power and the temperature deviation value, the heating value trend value of the battery cell system is obtained.

[0070] Among them, the charging and discharging instructions are issued by the energy storage monitoring platform, and the rated operating power is set by the energy storage system.

[0071] Specifically, it can be seen from the above that the temperature deviation value can be expressed as e(t), and e(t)-e(t-1) represents the size of the differential control action, which can be expressed as ec(t'). ec(t') represents the heating trend of the battery system within a certain period of time. The larger the ec(t'), the greater the difference between the actual temperature value of the battery system and the cooling target temperature value based on historical data analysis. And in the application process of the actual energy storage system, the size of the heating value of the battery system is determined by the charging and discharging power of the battery system. The greater the charging and discharging power of the battery system, the greater the heating value, and the greater the cooling amount required to achieve the cooling target temperature value; the smaller the charging and discharging power of the battery system, the smaller the heating value, and the smaller the cooling amount required to achieve the cooling target temperature value. Directly determining the heating trend value of the battery system based on ec(t') can only be analyzed and predicted based on the historical cooling effect of the battery system, which has a large lag and has not been integrated with other monitoring platforms of the energy storage system to form an overall linkage. Therefore, the energy storage monitoring platform is introduced here. The energy storage monitoring platform can issue charging and discharging instructions based on monitoring generation and discharge, and then obtain the heating trend value of the battery system according to the charging and discharging instructions, the rated operating power of the energy storage system and the temperature deviation value of the liquid cooling unit. The specific expression is as follows:

[0072]

[0073] Among them, Pcmd is the charge and discharge instruction sent by the energy storage monitoring platform to the liquid cooling unit; Psum t is the rated operating power of the energy storage system, that is, the amount of electric power that the energy storage system can continuously output or absorb, usually in kilowatts (kW). The rated power not only reflects the technical level of the energy storage equipment, but is also an important guarantee for the performance and safety of the equipment; e(t) is the temperature deviation value of the liquid cooling unit at time t, and e(t-1) is the temperature deviation value of the liquid cooling unit at time t-1.

[0074] The above operation obtains the charging and discharging instructions and the rated operating power of the energy storage system, combined with the temperature deviation value of the liquid cooling unit, to obtain the heating trend value of the battery system, so that the liquid cooling unit can better control the temperature of the battery system in the later stage.

[0075] The above step S103, namely "obtaining control parameters according to the temperature deviation value, the heating value trend value and the preset fuzzy control model", is described in detail below in conjunction with the embodiments.

[0076] The temperature deviation value and the calorific value trend value are divided into domains respectively to obtain the temperature deviation value domain and the calorific value trend value domain; according to the temperature deviation value domain, the calorific value trend value domain and the membership functions corresponding to each domain, the temperature deviation membership parameter and the calorific value trend membership parameter are obtained; according to the temperature deviation membership parameter, the calorific value trend membership parameter and the preset fuzzy control model, the control parameter is obtained.

[0077] Among them, the fuzzy control model can be a fuzzy controller.

[0078] Here, the fuzzy controller can have two inputs: temperature deviation value e(t) and heating value trend value ec(t). In the domain of the variable temperature deviation value e(t), it can be divided into 7 regions, namely {-6~-4; -4~-2; -2~0; 0~2; 2~4; 4~6}, which represent 7 fuzzy subsets: negative big NB (Negative Big); negative medium NM (Negative Medium); negative small NS (Negative Small); zero ZE or Z0 (Zero); positive small PS (Positive Small); positive medium PM (Positive Medium); positive big PB (Positive Big). The membership function of e(t) can adopt triangular membership function or Gaussian membership function, as shown in the following example. Figure 2 shown.

[0079] In the domain of the trend value of the variable calorific value ec(t), it can also be divided into 7 regions, namely {-1.5~-1; -1~-0.5; -0.5~0; 0~0.5; 0.5~1; 1~1.5}, which respectively represent 7 fuzzy subsets: Negative Big NB (Negative Big); Negative Medium NM (Negative Medium); Negative Small NS (Negative Small); Zero ZE or Z0 (Zero); Positive Small PS (Positive Small); Positive Medium PM (Positive Medium); Positive Big PB (Positive Big). The membership function of ec(t) can also adopt a triangular membership function or a Gaussian membership function, as shown in the following example. Figure 3 shown.

[0080] According to the temperature deviation value domain, the calorific value trend value domain and the membership functions corresponding to each domain, the temperature deviation membership parameter and the calorific value trend membership parameter are obtained.

[0081] Here, combined Figure 2 and Figure 3Let's take an example. Assuming that the temperature deviation value corresponds to the domain interval of -6 to -4, that is, NB, there are three corresponding curves, NB, NM and NS. Based on these three curves, the corresponding membership parameters can be obtained. Assuming that the calorific value trend corresponds to the domain interval of -1.5 to -1, that is, NB, there are three corresponding curves, NB, NM and NS. Based on these three curves, the corresponding membership parameter values ​​can be obtained.

[0082] The control parameters are obtained according to the temperature deviation membership parameter, the heating value trend membership parameter and the preset fuzzy control model.

[0083] As a feasible method, the domain of each control parameter is divided to obtain the domain of each control parameter and the corresponding membership function; according to the temperature deviation membership parameter, the heating value trend membership parameter, the preset fuzzy rule table, the domain of each control parameter and the corresponding membership function, the membership value and the individual value of each membership function belonging to different control parameter domain intervals are obtained; according to the domain of each control parameter, the corresponding membership function, the corresponding membership value, the corresponding individual value and the preset fuzzy formula, the corresponding control parameter is obtained.

[0084] Among them, the control parameters include K p , K i and K d The preset fuzzy control model includes a preset fuzzy rule table. By continuously detecting the changes of e(t) and ec(t), the corresponding control parameter K is obtained based on the preset fuzzy rule table. p , K i and K d .

[0085] Specifically, the domain of each control parameter is divided to obtain the domain of each control parameter and the corresponding membership function. p It can also be divided into 7 regions, namely {-0.75~-0.5; -0.5~-0.25; -0.25~0; 0~0.25; 0.25~0.5; 0.5~0.75}, representing 7 fuzzy subsets: negative large NB; negative medium NM; negative small NS; zero Z0; positive small PS; positive medium PM; positive large PB. p The membership function of can also be a triangular membership function or a Gaussian membership function, as shown in Figure 4 shown.

[0086] For the control parameter K i, can also be divided into 7 regions, namely {-0.06~-0.04; -0.04~-0.02; -0.02~0; 0~0.02; 0.02~0.04; 0.04~0.06}, representing 7 fuzzy subsets: negative large NB; negative medium NM; negative small NS; zero Z0; positive small PS; positive medium PM; positive large PB. i The membership function of can also be a triangular membership function or a Gaussian membership function, as shown in Figure 5 shown.

[0087] For the control parameter K d , can also be divided into 7 regions, namely {-0.6~-0.4; -0.4~-0.2; -0.2~0; 0~0.2; 0.2~0.4; 0.4~0.6}, representing 7 fuzzy subsets: negative large NB; negative medium NM; negative small NS; zero Z0; positive small PS; positive medium PM; positive large PB. K d The membership function of can also be a triangular membership function or a Gaussian membership function, as shown in Figure 6 shown.

[0088] According to the temperature deviation membership parameter, the heating value trend membership parameter, the preset fuzzy rule table, the control parameter domain and the corresponding membership function, the membership value and the number of values ​​of each membership function belonging to different control parameter domain intervals are obtained. Here, due to the proportional factor K between the temperature deviation value e(t) and the heating value trend value ec(t) p Execute the following association logic. a) If e(t) and ec(t) have the same direction and are both negative, the smaller the sum of the two, the greater the K p The larger the control parameter is; b) If the two are in opposite directions, as the sum of the two approaches 0, K P The closer the control parameter is to 0; c) If the two directions are the same and both are positive, the larger the sum of the two, K p The smaller the control parameter is. Therefore, K P The preset fuzzy rule table is as follows:

[0089]

[0090] Due to the proportional factor K between the temperature deviation value e(t) and the calorific value ec(t) i Execute the following association logic. a) If e(t) and ec(t) have the same direction and are both positive, the larger the sum of the two, the higher K i The larger the control parameter is; b) If the two are in opposite directions; As the sum of the two approaches 0, K i The closer the control parameter is to 0; c) If the two are in the same direction and both are negative, the larger the sum of the two, the higher the K i The smaller the control parameter is. Therefore, K iThe preset fuzzy rule table is as follows:

[0091]

[0092] Due to the proportional factor K between the temperature deviation value e(t) and the calorific value ec(t) d The following related logic is executed. a) In the early stage of adjustment, the differential effect should be increased to avoid overshoot; b) In the middle stage of adjustment, due to the adjustment characteristics of K d The control parameters are sensitive to changes, so K d The control parameter should be appropriately smaller and should remain fixed; c) In the later stage of adjustment, K d The control parameters should be reduced to reduce the braking effect of the controlled process and compensate for the initial adjustment process due to K d The larger the control parameter, the longer the adjustment process will take. d The preset fuzzy rule table is as follows:

[0093]

[0094] Specifically, the control parameter K p For example, assuming e(t) = -5, ec(t) = -1.2, based on Figure 2 The membership function curve corresponding to e(t) can be approximately 0.9NB, 0.6NM and 0.3NS; based on Figure 3 The membership function curve corresponding to ec(t) can be approximately 0.8NB, 0.7NM and 0.3NS; Substitute the corresponding membership parameters obtained above into K p The corresponding preset fuzzy rule table can be expressed as follows:

[0095]

[0096] Assume that the control parameter K p The membership value of can be expressed by m, then the expression of m is as follows:

[0097] m=(0.72*PB+0.48*PB+0.63*PB+0.42*PB)+(0.24*PM+0.21*PM+0.27*PM+0.18*PM+0.09*PM)=2.25*PB+0.99*PM.

[0098] From the above, we can get the control parameter K p The corresponding membership values ​​are 2.45 and 0.99, and the number of values ​​is 2, namely PB and PM.

[0099] According to the domain of each control parameter, the corresponding membership function, the corresponding membership value, the corresponding numerical value and the preset fuzzy formula, the corresponding control parameter is obtained. Since the input value of the PID controller needs to be a specific numerical value, the control parameter K can be p , K i and K d Defuzzification processing is performed. The present application can use the centroid method to defuzzify the control parameters, and the specific preset fuzzification formula can be expressed as follows:

[0100]

[0101] Among them, n represents the corresponding numerical value; m represents the membership value of the control parameter belonging to different intervals; l and h represent the upper and lower limits of the domain interval corresponding to the control parameter; k represents the membership function corresponding to the control parameter.

[0102] Here, the control parameter K is still used p For example, from the above, we can see that when e(t) = -5, ec(t) = -1.2, we can get m as 2.25 and 0.99 respectively, and the values ​​are PB and PM. And by Figure 4 It can be seen that the interval corresponding to PM is 0.25~0.5; the interval corresponding to PB is 0.5~0.75. The membership functions corresponding to PM and PB are assumed to be represented by k1 and k2, then the control parameter K p The specific expression is:

[0103]

[0104]

[0105] By analogy, the corresponding control parameter K can be obtained p , K i and K d The specific value of .

[0106] The above operation obtains each control parameter based on the fuzzy controller and the fuzzy formula, thereby achieving the effect of improving the accuracy of each control parameter.

[0107] Next, the above step 105, namely "obtaining a target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameters and the preset controller model" is described in detail in conjunction with the embodiment.

[0108] As a feasible method, the control coefficient corresponding to each control parameter is obtained according to each control parameter and the control cycle of the liquid cooling unit; the target temperature value of the liquid cooling unit is obtained according to the temperature deviation value, each control coefficient, the control cycle and the preset controller model.

[0109] Here, it is considered that the liquid cooling unit has a certain control cycle in actual use. At the same time, the liquid cooling unit is a system with high time lag; therefore, n minutes can be set as a control cycle, represented by T. According to each control parameter and the control cycle of the liquid cooling unit, the control coefficient corresponding to each control parameter is obtained, and its specific expression is as follows:

[0110] K p =k p

[0111]

[0112] According to the temperature deviation value, each control coefficient, control cycle and preset controller model, the specific expression of the target temperature value of the liquid cooling unit is as follows:

[0113]

[0114] Where, e(t) represents the temperature deviation value; T i , T d and k p are also known, from which the target temperature value u(t) of the liquid cooling unit can be obtained.

[0115] Through the above operations, the target temperature value of the liquid cooling unit is obtained based on the PID controller, and then the operating gear of the liquid cooling unit can be controlled in combination with the target temperature value in the later stage, so as to improve the safety of the battery system and extend the life of the overall energy storage system.

[0116] Finally, the above step 107 of “adjusting the operating gear of the liquid cooling unit according to the target temperature value, the water outlet temperature value and the preset comparison threshold value” is described in detail in conjunction with the embodiment.

[0117] As a feasible method, a temperature difference value is obtained according to the target temperature value and the water outlet temperature value; the absolute value of the temperature difference value is compared with a first comparison threshold value; when the absolute value of the temperature difference value is greater than or equal to the first comparison threshold value, the operating gear of the liquid cooling unit is increased.

[0118] The preset comparison threshold includes a first comparison threshold, and the first comparison threshold is generally set to 2 degrees.

[0119] Here, since the outlet temperature value of the liquid cooling unit can be directly obtained, and the target temperature value of the liquid cooling unit has also been obtained based on the PID controller and the fuzzy controller, the target temperature value of the liquid cooling unit and the outlet temperature value can be differenced to obtain the temperature difference value. Specifically, the outlet temperature value of the liquid cooling unit can be represented by w(t), and the target temperature value of the liquid cooling unit can be represented by u(t). The difference between w(t) and u(t) is calculated, that is, w(t)-u(t)=Δt. The absolute value of Δt is calculated, that is, |Δt|, and the absolute value of the temperature difference is compared with the first comparison threshold. When the absolute value of the temperature difference is greater than or equal to the first comparison threshold, that is, |Δt|>=2, the operating gear of the liquid cooling unit is increased.

[0120] In another feasible manner, when the absolute value of the temperature difference is less than the first comparison threshold, the absolute value of the temperature difference is compared with the second comparison threshold; when the absolute value of the temperature difference is less than the first comparison threshold but greater than or equal to the second comparison threshold, the current state of the liquid cooling unit is maintained; when the absolute value of the temperature difference is less than the second comparison threshold, the operating gear of the liquid cooling unit is reduced.

[0121] The preset comparison threshold also includes a second comparison threshold, and the second comparison threshold is generally set to 1 degree.

[0122] Here, when the absolute value of the temperature difference is less than the first comparison threshold, that is, |Δt|<2, the absolute value of the temperature difference is compared with the second comparison threshold. When the absolute value of the temperature difference is less than the first comparison threshold but greater than or equal to the second comparison threshold, that is, 1=<|Δt|<2, the current state of the liquid cooling unit is maintained, indicating that the liquid cooling unit is currently in the optimal state; when the absolute value of the temperature difference is less than the second comparison threshold, that is, |Δt|<1, the operating gear of the liquid cooling unit is reduced.

[0123] In the above operation, when the difference between the outlet temperature value of the liquid cooling unit and the target temperature value is larger than 2 degrees, it means that the liquid cooling unit itself has not reached the set optimal working range. At this time, the operating gear of the liquid cooling unit can be increased to achieve the effect of increasing the coolant temperature and reducing the operating speed; when the difference between the outlet temperature value of the liquid cooling unit and the target temperature value is small, less than 1 degree, the operating gear of the liquid cooling unit can be reduced to achieve the effect of reducing power consumption.

[0124] In combination with the implementation method in the above embodiment, Figure 7 An example of a preferred method flow provided in the embodiment of the present application is described. Figure 7 As shown, the method may include the following steps:

[0125] Step S201, obtaining a temperature deviation value, where the temperature deviation value refers to a difference between a cooling target value of a liquid cooling unit and an actual temperature output value of a battery cell system.

[0126] Step S202, obtaining charging and discharging instructions and rated operating power, wherein the charging and discharging instructions are issued by the energy storage monitoring platform, and the rated operating power is set by the energy storage system.

[0127] Step S203, obtaining a heating value trend value of the battery cell system according to the charge and discharge instructions, the rated operating power and the temperature deviation value.

[0128] Step S204, dividing the temperature deviation value and the calorific value trend value into domains respectively to obtain a temperature deviation value domain and a calorific value trend value domain.

[0129] Step S205 , obtaining a temperature deviation membership parameter and a heating value trend membership parameter according to the temperature deviation value domain, the heating value trend value domain and the membership functions corresponding to each domain.

[0130] Step S206, the preset fuzzy control model includes a preset fuzzy rule table, and there are multiple control parameters; the domain of each control parameter is divided to obtain the domain of each control parameter and the corresponding membership function.

[0131] Step S207, according to the temperature deviation membership parameter, the heating value trend membership parameter, the preset fuzzy rule table, each control parameter domain and the corresponding membership function, obtain the membership value and the number of values ​​of each membership function belonging to different control parameter domain intervals.

[0132] Step S208, obtaining the corresponding control parameter according to the domain of each control parameter, the corresponding membership function, the corresponding membership value, the corresponding numerical value and the preset fuzzification formula.

[0133] Step S209, obtaining control coefficients corresponding to the control parameters according to the control parameters and the control cycle of the liquid cooling unit.

[0134] Step S210, obtaining a target temperature value of the liquid cooling unit according to the temperature deviation value, each control coefficient, the control period and a preset controller model.

[0135] Step S211, obtaining the water outlet temperature value of the liquid cooling unit, and obtaining the temperature difference value according to the target temperature value and the water outlet temperature value.

[0136] Step S212, comparing the absolute value of the temperature difference with the first comparison threshold, when the absolute value of the temperature difference is greater than or equal to the first comparison threshold, executing step S213; when the absolute value of the temperature difference is less than the first comparison threshold, executing step S14;

[0137] Step S213, raising the operating gear of the liquid cooling unit.

[0138] Step S214, comparing the absolute value of the temperature difference with the second comparison threshold, when the absolute value of the temperature difference is less than the first comparison threshold but greater than or equal to the second comparison threshold, executing step S15; when the absolute value of the temperature difference is less than the second comparison threshold, executing step S16;

[0139] Step S215, maintaining the current state of the liquid cooling unit.

[0140] Step S216, lowering the operating gear of the liquid cooling unit.

[0141] It should be understood that although Figure 1 , Figure 7 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in the application, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 , Figure 7 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0142] Figure 8 A schematic diagram of the structure of an electrochemical energy storage control device provided in an embodiment of the present application, which can be set in a computer device to perform the following operations: Figure 1 , Figure 7 The method flow shown in Figure 8 As shown, the device may include: a first acquisition module 301, a first calculation module 303, a second calculation module 305, and an output adjustment module 307. The main functions of each component module are as follows:

[0143] A first acquisition module 301 is used to acquire a temperature deviation value and a heating value trend value of a battery cell system, wherein the temperature deviation value refers to a difference between a cooling target value of a liquid cooling unit and an actual temperature output value of the battery cell system;

[0144] A first calculation module 303 is used to obtain control parameters according to the temperature deviation value, the heating value trend value and a preset fuzzy control model;

[0145] The second calculation module 305 is used to obtain the target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameter and the preset controller model;

[0146] The output adjustment module 307 is used to obtain the water outlet temperature value of the liquid cooling unit, and adjust the operating gear of the liquid cooling unit according to the target temperature value, the water outlet temperature value and the preset comparison threshold.

[0147] In one embodiment, the first acquisition module 301 is further used to:

[0148] Obtain charging and discharging instructions and rated operating power. The charging and discharging instructions are issued by the energy storage monitoring platform, and the rated operating power is set by the energy storage system;

[0149] According to the charge and discharge instructions, rated operating power and temperature deviation value, the heating value of the battery system is obtained.

[0150] In one embodiment, the first calculation module 303 is further configured to:

[0151] The temperature deviation value and the calorific value trend value are divided into domains respectively, and the temperature deviation value domain and the calorific value trend value domain are obtained;

[0152] According to the temperature deviation value domain, the calorific value trend value domain and the membership functions corresponding to each domain, the temperature deviation membership parameter and the calorific value trend membership parameter are obtained;

[0153] The control parameters are obtained according to the temperature deviation membership parameter, the heating value trend membership parameter and the preset fuzzy control model.

[0154] In one embodiment, the first calculation module 303 is further configured to:

[0155] Divide the domain of each control parameter to obtain the domain of each control parameter and the corresponding membership function;

[0156] According to the temperature deviation membership parameter, the heating value trend membership parameter, the preset fuzzy rule table, the control parameter domains and the corresponding membership functions, the membership value and the individual value of each membership function belonging to different control parameter domain intervals are obtained.

[0157] The corresponding control parameters are obtained according to the domain of each control parameter, the corresponding membership functions, the corresponding membership values, the corresponding numerical values ​​and the preset fuzzy formula.

[0158] In one embodiment, the second calculation module 305 is further configured to:

[0159] According to each control parameter and the control cycle of the liquid cooling unit, the control coefficient corresponding to each control parameter is obtained;

[0160] According to the temperature deviation value, each control coefficient, the control period and the preset controller model, the target temperature value of the liquid cooling unit is obtained.

[0161] In one embodiment, the preset comparison threshold includes a first comparison threshold, and the output adjustment module 307 is further used to:

[0162] According to the target temperature value and the outlet temperature value, the temperature difference value is obtained;

[0163] Comparing the absolute value of the temperature difference with a first comparison threshold;

[0164] When the absolute value of the temperature difference is greater than or equal to the first comparison threshold, the operating gear of the liquid cooling unit is increased.

[0165] In one embodiment, the preset comparison threshold value further includes a second comparison threshold value, and the output adjustment module 307 is further used to:

[0166] When the absolute value of the temperature difference is less than the first comparison threshold, the absolute value of the temperature difference is compared with the second comparison threshold;

[0167] When the absolute value of the temperature difference is less than the first comparison threshold but greater than or equal to the second comparison threshold, maintaining the current state of the liquid cooling unit;

[0168] When the absolute value of the temperature difference is less than the second comparison threshold, the operating gear of the liquid cooling unit is reduced.

[0169] The same or similar parts between the above embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0170] It should be noted that the embodiments of the present application may involve the use of user data. In actual applications, user-specific personal data can be used in the scheme described in this article within the scope permitted by applicable laws and regulations, provided that the applicable laws and regulations of the country are met (for example, the user's explicit consent, effective notification to the user, and the user's explicit authorization, etc.).

[0171] According to an embodiment of the present application, the present application also provides a computer device and a computer-readable storage medium.

[0172] like Fig. 9 , is a block diagram of a computer device according to an embodiment of the present application. The computer device is intended to represent various forms of digital computers or mobile devices. The digital computer may include a desktop computer, a portable computer, a workbench, a personal digital assistant, a server, a mainframe computer, and other suitable computers. The mobile device may include a tablet computer, a smart phone, a wearable device, etc.

[0173] like Fig. 9As shown, the device 400 includes a computing unit 401, a ROM 402, a RAM 403, a bus 404, and an input / output (I / O) interface 405, which are connected to each other via the bus 404. The input / output (I / O) interface 405 is also connected to the bus 404.

[0174] The computing unit 401 can perform various processes in the method embodiment of the present application according to the computer instructions stored in the read-only memory (ROM) 402 or the computer instructions loaded from the storage unit 408 to the random access memory (RAM) 403. The computing unit 401 can be various general and / or special processing components with processing and computing capabilities. The computing unit 401 may include, but is not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. In some embodiments, the method provided in the embodiment of the present application can be implemented as a computer software program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 408.

[0175] RAM 403 may also store various programs and data required for the operation of device 400. Part or all of a computer program may be loaded and / or installed onto device 400 via ROM 402 and / or communication unit 409.

[0176] The input unit 406, output unit 407, storage unit 408 and communication unit 409 in the device 400 can be connected to the I / O interface 405. The input unit 406 can be, for example, a keyboard, a mouse, a touch screen, a microphone, etc. The output unit 407 can be, for example, a display, a speaker, an indicator light, etc. The device 400 can exchange information, data, etc. with other devices through the communication unit 409.

[0177] It should be noted that the device may also include other components necessary for normal operation, or may only include components necessary for implementing the solution of the present application, rather than all the components shown in the figure.

[0178] Various implementations of the systems and techniques described herein can be realized in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof.

[0179] The computer instructions for implementing the method of the present application can be written in any combination of one or more programming languages. These computer instructions can be provided to the computing unit 401, so that when the computer instructions are executed by the computing unit 401 such as a processor, the steps involved in the method embodiment of the present application are executed.

[0180] The computer-readable storage medium provided in the present application may be a tangible medium that may contain or store computer instructions for executing the steps involved in the method embodiments of the present application. The computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, and other forms of storage media.

[0181] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A control method for an electrochemical energy storage liquid cooling unit, characterized in that: The method comprises: Obtaining a temperature deviation value and a heating value trend value of the battery cell system, wherein the temperature deviation value refers to the difference between a cooling target value of the liquid cooling unit and an actual temperature output value of the battery cell system; Obtaining control parameters according to the temperature deviation value, the heating value trend value and a preset fuzzy control model; Obtaining a target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameter and a preset controller model; The water outlet temperature value of the liquid cooling unit is obtained, and the operating gear of the liquid cooling unit is adjusted according to the target temperature value, the water outlet temperature value and a preset comparison threshold.

2. The method according to claim 1, characterized in that The obtaining of the heating value trend value of the battery cell system includes: Obtaining charging and discharging instructions and rated operating power, wherein the charging and discharging instructions are issued by the energy storage monitoring platform, and the rated operating power is set by the energy storage system; A heating value trend value of a battery cell system is obtained according to the charge and discharge instructions, the rated operating power and the temperature deviation value.

3. The method according to claim 1, characterized in that The control parameters are obtained according to the temperature deviation value, the heating value trend value and the preset fuzzy control model, including: Dividing the temperature deviation value and the calorific value trend value into domains respectively to obtain a temperature deviation value domain and a calorific value trend value domain; According to the temperature deviation value domain, the calorific value trend value domain and the membership functions corresponding to each domain, a temperature deviation membership parameter and a calorific value trend membership parameter are obtained; The control parameter is obtained according to the temperature deviation membership parameter, the heating value trend membership parameter and the preset fuzzy control model.

4. The method according to claim 3, characterized in that The preset fuzzy control model includes a preset fuzzy rule table, and the control parameters include multiple ones; the control parameters are obtained according to the temperature deviation membership parameter, the heating value trend membership parameter and the preset fuzzy control model, including: Dividing the domain of each control parameter to obtain the domain of each control parameter and the corresponding membership function; According to the temperature deviation membership parameter, the heating value trend membership parameter, the preset fuzzy rule table, each control parameter domain and the corresponding membership function, the membership value and the number of values ​​of each membership function belonging to different control parameter domain intervals are obtained; The corresponding control parameter is obtained according to the domain of each control parameter, the corresponding membership function, the corresponding membership value, the corresponding numerical value and the preset fuzzification formula.

5. The method according to claim 4, characterized in that The step of obtaining a target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameter and the preset controller model includes: According to each of the control parameters and the control period of the liquid cooling unit, a control coefficient corresponding to each of the control parameters is obtained; A target temperature value of the liquid cooling unit is obtained according to the temperature deviation value, each of the control coefficients, the control period and the preset controller model.

6. The method according to any one of claims 1 to 5, characterized in that: The preset comparison threshold includes a first comparison threshold, and adjusting the operating gear of the liquid cooling unit according to the target temperature value, the water outlet temperature value and the preset comparison threshold includes: Obtaining a temperature difference value according to the target temperature value and the water outlet temperature value; Comparing the absolute value of the temperature difference with the first comparison threshold; When the absolute value of the temperature difference is greater than or equal to the first comparison threshold, the operating gear of the liquid cooling unit is increased.

7. The method according to claim 6, characterized in that The preset comparison threshold value further includes a second comparison threshold value, and the method further includes: When the absolute value of the temperature difference is less than the first comparison threshold, comparing the absolute value of the temperature difference with the second comparison threshold; When the absolute value of the temperature difference is less than the first comparison threshold but greater than or equal to the second comparison threshold, maintaining the current state of the liquid cooling unit; When the absolute value of the temperature difference is less than the second comparison threshold, the operating gear of the liquid cooling unit is reduced.

8. An electrochemical energy storage liquid cooling unit control device, characterized in that: The device comprises: A first acquisition module is used to acquire a temperature deviation value and a heating value trend value of the battery system, wherein the temperature deviation value refers to the difference between a cooling target value of the liquid cooling unit and an actual temperature output value of the battery system; A first calculation module, used for obtaining a control parameter according to the temperature deviation value, the heating value trend value and a preset fuzzy control model; A second calculation module, used for obtaining a target temperature value of the liquid cooling unit according to the temperature deviation value, the control parameter and a preset controller model; The output adjustment module is used to obtain the water outlet temperature value of the liquid cooling unit, and adjust the operating gear of the liquid cooling unit according to the target temperature value, the water outlet temperature value and a preset comparison threshold.

9. A computer device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores computer instructions that can be executed by the at least one processor, and the computer instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer instructions stored thereon, characterized in that: The computer instructions are used to make a computer execute the method according to any one of claims 1 to 7.

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