Control method of power cabinet temperature control system and terminal

Abstract

The invention relates to the technical field of temperature management, in particular to a control method of a power cabinet temperature control system and a terminal, according to a pre-divided temperature zone and a preset sampling period, operating parameters are respectively collected, and the operating parameters comprise the environment temperature, the power of the temperature control system and the temperature of the temperature zone; constructing an incremental PID controller model, and calculating an adjustment control quantity in combination with the operation parameters collected recently for a preset number of times; adjusting the operation power of the temperature control system according to the adjustment control quantity; according to the method, the temperature zones are divided, the environment temperature and the temperature zone temperature are collected periodically, and the control quantity is calculated and adjusted through the data of the recent period and the incremental PID controller model, so that the operation power of the temperature control system is adjusted in real time, the better temperature control effect is achieved, and power consumption is reduced; and a fuzzy self-adaptive setting parameter is introduced into the incremental PID controller model, so that the influence of equipment use time, environmental interference and the like is effectively inhibited, and a better temperature control effect is achieved.

Description

[0001] This case is a divisional application based on the invention patent with application date of July 24, 2024, application number 202410993552.0, and name "A method and device for controlling the working temperature of a power cabinet" as the parent case. Technical Field

[0002] The present invention relates to the technical field of temperature management, and in particular to a control method and a terminal for a temperature control system of a power cabinet. Background Art

[0003] At present, the new energy vehicle industry is booming, and the technology of new energy vehicles is constantly iterating. New energy vehicles with different battery voltage platforms, different charging powers, and different driving ranges are constantly pouring into the market. The charging and testing power cabinet needs to meet their different charging needs while ensuring its own good operation and low enough power consumption and noise. Therefore, an excellent temperature control system is urgently needed for the charging and testing power cabinet.

[0004] At present, the existing temperature control system generally has the following three situations: (1) Simply turning the temperature control system on or off based on the upper and lower temperature limits.

[0005] (2) Whether to turn the temperature control system on or off is determined solely based on whether the vehicle is charging.

[0006] (3) The temperature control system is turned on simply based on the decision to have a vehicle charging, and is turned off after being forced to run for a certain period of time without a vehicle charging.

[0007] That is, the temperature control strategy of the current temperature control system is relatively mechanical, the temperature control effect is poor, and it is easy to increase energy consumption. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide a control method and a terminal for a temperature control system of a power cabinet, so as to achieve a better temperature control effect and reduce power consumption.

[0009] In order to solve the above technical problems, the technical solution adopted by the present invention is: A control method for a power cabinet temperature control system comprises the following steps: S1. According to the pre-divided temperature zones, operating parameters are collected respectively according to the preset sampling period, wherein the operating parameters include the ambient temperature, the power of the temperature control system and the temperature of the temperature zone; S2, constructing an incremental PID controller model, and calculating the adjustment control amount in combination with the operating parameters collected at the latest preset number of times; The preset number of times is 3 times, and the incremental PID controller model is expressed as follows: ΔP=A*e n +B*e n-1+C*e n-2 ; A=K P (1+T / T i +T d / T); B=-K P (1+2T d / T); C=K P *T d / T; Among them, A, B and C represent control constants, e n 、e n-1 and e n-2 Indicates the deviation signal within the last three sampling cycles. The deviation signal is the difference between the temperature in the temperature zone and the preset target temperature. K P represents the fuzzy adaptive tuning parameter, T i Indicates the integral coefficient, T d represents the differential coefficient; S3, adjusting the operating power of the temperature control system according to the adjustment control amount; When the temperature of the temperature zone is lower than the target temperature or is within a preset range of the target temperature, it is determined whether the vehicle is being charged, and if so, the temperature control system is maintained, otherwise, the temperature control system is shut down.

[0010] In order to solve the above technical problems, the technical solution adopted by the present invention is: A method for controlling the operating temperature of a power cabinet comprises the following steps: S1. According to the pre-divided temperature zones, operating parameters are collected respectively according to the preset sampling period, wherein the operating parameters include the ambient temperature, the power of the temperature control system and the temperature of the temperature zone; S2, constructing an incremental PID controller model, and calculating the adjustment control amount in combination with the operating parameters collected at the latest preset number of times; The preset number of times is 3 times, and the incremental PID controller model is expressed as follows: ΔP=A*e n +B*e n-1 +C*e n-2 ; A=K P (1+T / T i +T d / T); B=-K P (1+2T d / T); C=K P *T d / T; Among them, A, B and C represent control constants, en 、e n-1 and e n-2 Indicates the deviation signal within the last three sampling cycles. The deviation signal is the difference between the temperature in the temperature zone and the preset target temperature. K P represents the fuzzy adaptive tuning parameter, T i Indicates the integral coefficient, T d represents the differential coefficient; S3. Adjust the operating power of the temperature control system according to the adjustment control amount.

[0011] In order to solve the above technical problems, another technical solution adopted by the present invention is: A control device for a power cabinet temperature control system includes a processor, a memory, and an ARM program stored in the memory and executable on the processor. When the processor executes the ARM program, the following steps are implemented: S1. According to the pre-divided temperature zones, operating parameters are collected respectively according to the preset sampling period, wherein the operating parameters include the ambient temperature, the power of the temperature control system and the temperature of the temperature zone; S2, constructing an incremental PID controller model, and calculating the adjustment control amount in combination with the operating parameters collected at the latest preset number of times; The preset number of times is 3 times, and the incremental PID controller model is expressed as follows: ΔP=A*e n +B*e n-1 +C*e n-2 ; A=K P (1+T / T i +T d / T); B=-K P (1+2T d / T); C=K P *T d / T; Among them, A, B and C represent control constants, e n 、e n-1 and e n-2 Indicates the deviation signal within the last three sampling cycles. The deviation signal is the difference between the temperature in the temperature zone and the preset target temperature. K P represents the fuzzy adaptive tuning parameter, T i Indicates the integral coefficient, T d represents the differential coefficient; S3, adjusting the operating power of the temperature control system according to the adjustment control amount; When the temperature of the temperature zone is lower than the target temperature or is within a preset range of the target temperature, it is determined whether the vehicle is being charged, and if so, the temperature control system is maintained, otherwise, the temperature control system is shut down.

[0012] In order to solve the above technical problems, another technical solution adopted by the present invention is: A device for controlling the working temperature of a power cabinet comprises a processor, a memory, and an ARM program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the ARM program: S1. According to the pre-divided temperature zones, operating parameters are collected respectively according to the preset sampling period, wherein the operating parameters include the ambient temperature, the power of the temperature control system and the temperature of the temperature zone; S2, constructing an incremental PID controller model, and calculating the adjustment control amount in combination with the operating parameters collected at the latest preset number of times; The preset number of times is 3 times, and the incremental PID controller model is expressed as follows: ΔP=A*e n +B*e n-1 +C*e n-2 ; A=K P (1+T / T i +T d / T); B=-K P (1+2T d / T); C=K P *T d / T; Among them, A, B and C represent control constants, e n 、e n-1 and e n-2 Indicates the deviation signal within the last three sampling cycles. The deviation signal is the difference between the temperature in the temperature zone and the preset target temperature. K P represents the fuzzy adaptive tuning parameter, T i Indicates the integral coefficient, T d represents the differential coefficient; S3. Adjust the operating power of the temperature control system according to the adjustment control amount.

[0013] The beneficial effects of the present invention are as follows: a control method and terminal for a power cabinet temperature control system of the present invention divide temperature zones, periodically collect ambient temperature and temperature zone temperature, and calculate the adjustment control amount through the data of the most recent cycle and the incremental PID controller model, thereby adjusting the operating power of the temperature control system in real time to achieve better temperature control effects and reduce power consumption. Fuzzy adaptive tuning parameters are introduced into the incremental PID controller model to effectively suppress the influence of equipment usage time, environmental interference, etc., to achieve better temperature control effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A flow chart of a method for controlling the operating temperature of a power cabinet according to an embodiment of the present invention; Figure 2 A structural diagram of a device for controlling the working temperature of a power cabinet according to an embodiment of the present invention; Figure 3 A model example diagram of a method for controlling the operating temperature of a power cabinet according to an embodiment of the present invention; Description of labels: 1. A device for controlling the working temperature of a power cabinet; 2. A processor; 3. A memory. DETAILED DESCRIPTION

[0015] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0016] Please refer to Figure 1 as well as Figure 3 , a method for controlling the working temperature of a power cabinet, comprising the steps of: S1. According to the pre-divided temperature zones, operating parameters are collected respectively according to the preset sampling period, wherein the operating parameters include the ambient temperature, the power of the temperature control system and the temperature of the temperature zone; S2, constructing an incremental PID controller model, and calculating the adjustment control amount in combination with the operating parameters collected at the latest preset number of times; The preset number of times is 3 times, and the incremental PID controller model is expressed as follows: ΔP=A*e n +B*e n-1 +C*e n-2 ; A=K P (1+T / T i +T d / T); B=-K P (1+2T d / T); C=K P *T d / T; Among them, A, B and C represent control constants, e n 、e n-1 and e n-2 Indicates the deviation signal within the last three sampling cycles. The deviation signal is the difference between the temperature in the temperature zone and the preset target temperature. K P represents the fuzzy adaptive tuning parameter, T i Indicates the integral coefficient, T d represents the differential coefficient; S3. Adjust the operating power of the temperature control system according to the adjustment control amount.

[0017] From the above description, it can be seen that the beneficial effects of the present invention are: a method for controlling the working temperature of a power cabinet of the present invention divides temperature zones, periodically collects ambient temperature and temperature zone temperature, and uses the data of the most recent period and an incremental PID controller model to calculate the adjustment control quantity, thereby performing real-time adjustment on the operating power of the temperature control system to achieve better temperature control effects and reduce power consumption. Fuzzy adaptive tuning parameters are introduced into the incremental PID controller model to effectively suppress the influence of equipment usage time, environmental interference, etc., to achieve better temperature control effects.

[0018] Furthermore, the determination of the adaptive setting parameters is specifically as follows: With the current deviation signal e n and the deviation change △e as input, which is calculated by fuzzy adaptive tuning according to the preset fine-tuning value table; Where △e=e n -e n-1 ; According to the difference between the ambient temperature and the preset target temperature, the proportionality coefficient of the adaptive setting parameter after adjustment is determined, and the adaptive setting parameter is adjusted according to the proportionality coefficient.

[0019] From the above description, it can be seen that the demand control amount of the previous cycle is corrected according to the adjustment control amount calculated in the current cycle, and then the demand control amount of the current cycle is obtained, so as to control the operating power of the temperature control system.

[0020] Furthermore, the steps between step S1 and step S2 include: Determine whether the temperature of the temperature zone is less than the preset target temperature. If so, determine whether there is vehicle charging. If there is no vehicle charging, shut down the temperature control system without waiting for the command of the PID controller, otherwise enter step S2.

[0021] From the above description, it can be seen that if the current temperature is lower than the target temperature, the temperature control system is directly shut down without waiting for the command of the PID controller, thus achieving more efficient control.

[0022] Furthermore, the integration coefficient T i The value range is [240,480], and the differential coefficient T d The value range is [3,150].

[0023] It can be seen from the above description that the above values ​​of the integral coefficient and the differential coefficient are taken as a specific embodiment of the present invention.

[0024] Please refer to Figure 2 , a device for controlling the working temperature of a power cabinet, comprising a processor, a memory, and an ARM program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the ARM program: S1. According to the pre-divided temperature zones, operating parameters are collected respectively according to the preset sampling period, wherein the operating parameters include the ambient temperature, the power of the temperature control system and the temperature of the temperature zone; S2, constructing an incremental PID controller model, and calculating the adjustment control amount in combination with the operating parameters collected at the latest preset number of times; The preset number of times is 3 times, and the incremental PID controller model is expressed as follows: ΔP=A*e n +B*e n-1 +C*e n-2 ; A=K P (1+T / T i +T d / T); B=-K P (1+2T d / T); C=K P *T d / T; Among them, A, B and C represent control constants, e n 、e n-1 and e n-2 Indicates the deviation signal within the last three sampling cycles. The deviation signal is the difference between the temperature in the temperature zone and the preset target temperature. K P represents the fuzzy adaptive tuning parameter, T i Indicates the integral coefficient, T d represents the differential coefficient; S3. Adjust the operating power of the temperature control system according to the adjustment control amount.

[0025] From the above description, it can be seen that the beneficial effects of the present invention are: a method for controlling the working temperature of a power cabinet of the present invention divides temperature zones, periodically collects ambient temperature and temperature zone temperature, and uses the data of the most recent period and an incremental PID controller model to calculate the adjustment control quantity, thereby performing real-time adjustment on the operating power of the temperature control system to achieve better temperature control effects and reduce power consumption. Fuzzy adaptive tuning parameters are introduced into the incremental PID controller model to effectively suppress the influence of equipment usage time, environmental interference, etc., to achieve better temperature control effects.

[0026] Furthermore, the determination of the adaptive setting parameters is specifically as follows: With the current deviation signal e n and the deviation change △e as input, which is calculated by fuzzy adaptive tuning according to the preset fine-tuning value table; Where △e=e n -e n-1 ; According to the difference between the ambient temperature and the preset target temperature, the proportionality coefficient of the adaptive setting parameter after adjustment is determined, and the adaptive setting parameter is adjusted according to the proportionality coefficient.

[0027] From the above description, it can be seen that the fuzzy adaptive tuning parameters are calculated based on the deviation signal through fuzzy adaptive tuning.

[0028] Furthermore, step S3 is specifically as follows: Calculate the current demand control quantity P according to the adjustment control quantity n : P n =ΔP+P n-1 ; Among them, ΔP represents the adjustment control amount, P n-1 Indicates the demand control quantity of the previous sampling period; The operating power of the temperature control system is adjusted according to the demand control amount.

[0029] From the above description, it can be seen that the demand control amount of the previous cycle is corrected according to the adjustment control amount calculated in the current cycle, and then the demand control amount of the current cycle is obtained, so as to control the operating power of the temperature control system.

[0030] Furthermore, the steps between step S1 and step S2 include: Determine whether the temperature of the temperature zone is less than the preset target temperature. If so, determine whether there is vehicle charging. If there is no vehicle charging, shut down the temperature control system without waiting for the command of the PID controller, otherwise enter step S2.

[0031] From the above description, it can be seen that if the current temperature is lower than the target temperature, the temperature control system is directly shut down without waiting for the command of the PID controller, thus achieving more efficient control.

[0032] Furthermore, the integration coefficient T i The value range is [240,480], and the differential coefficient T d The value range is [3,150].

[0033] It can be seen from the above description that the above values ​​of the integral coefficient and the differential coefficient are taken as a specific embodiment of the present invention.

[0034] The present invention provides a method and device for controlling the working temperature of a power cabinet, which are suitable for controlling the temperature of a power cabinet.

[0035] Please refer to Figure 1 and Figure 3 , Embodiment 1 of the present invention is: A method for controlling the operating temperature of a power cabinet comprises the following steps: S1. According to the pre-divided temperature zones, operating parameters are collected respectively according to a preset sampling period, wherein the operating parameters include ambient temperature, temperature control system power, and temperature of the temperature zone.

[0036] In this embodiment, the power cabinet is divided into a plurality of different temperature zones, and relationships between the different temperature zones are established.

[0037] Periodically collect parameters such as ambient temperature, output power, and temperature zone temperature to control the temperature control system through comprehensive calculations.

[0038] The process can be referred to Figure 3 As shown in the figure, T1, T2, T3 are the temperature values ​​in the last three sampling cycles, △T1, △T2, △T3 are the deviation signals in the last three sampling cycles, P1 is the current demand control value, P2 is the demand control value in the previous cycle, △P is the control quantity that needs to be adjusted calculated by the incremental PID controller, K P Fuzzy adaptive tuning parameters.

[0039] S2, constructing an incremental PID controller model, and calculating the adjustment control amount in combination with the operating parameters collected at the latest preset number of times; In this embodiment, the preset number of times is 3 times, and the incremental PID controller model is expressed as follows: ΔP=A*e n +B*e n-1 +C*e n-2 ; A=K P (1+T / T i +T d / T); B=-K P (1+2T d / T); C=K P *T d / T; Among them, A, B and C represent control constants, e n 、e n-1 and e n-2 Indicates the deviation signal within the last three sampling cycles. The deviation signal is the difference between the temperature in the temperature zone and the preset target temperature. K P represents the fuzzy adaptive tuning parameter, T i Indicates the integral coefficient, T d represents the differential coefficient.

[0040] In this embodiment, the temperature change trend is distinguished by the short-term continuous temperature collection, the sampling period T and the deviation signal within the last three sampling periods included in the calculation are determined (in this embodiment, the sampling period is selected to be 5~10s, which can be adjusted according to actual needs in other equivalent embodiments), and the fuzzy adaptive setting parameter K is adjusted based on the difference between the ambient temperature and the target temperature. P .

[0041] The determination of the adaptive setting parameters is specifically as follows: With the current deviation signal e n and the deviation change △e as input, which is calculated by fuzzy adaptive tuning according to the preset fine-tuning value table; Where △e=e n -e n-1 ; According to the difference between the ambient temperature and the preset target temperature, the proportionality coefficient of the adaptive setting parameter after adjustment is determined, and the adaptive setting parameter is adjusted according to the proportionality coefficient.

[0042] In this embodiment, the current deviation signal e n And the deviation change △e is used as input, and seven value ranges are divided into negative large, negative medium, negative small, just right, positive small, positive medium, and positive large, and three parameters K are established. P \T i \T d The corresponding fine-tuning value table in the 7×7 value range is obtained by step-by-step table lookup and approximation. p The lower the temperature of the temperature zone is than the target temperature, the better the cooling effect is. p The smaller the temperature, the smaller the K after adjustment. pThe proportional coefficient of the value, and whether it needs to be relatively enlarged or reduced or not adjusted. If the ambient temperature is much lower than the set temperature, it will be reduced; if it is much higher, it will be enlarged; if the difference is not much, no adjustment will be made.

[0043] In this embodiment, the integral coefficient T i The value range is generally [240,480], and the differential coefficient T d The value range of is generally [3,150].

[0044] S3, adjusting the operating power of the temperature control system according to the adjustment control amount; Step S3 is specifically as follows: Calculate the current demand control quantity P according to the adjustment control quantity n : Pn=ΔP+P n-1 ; Among them, ΔP represents the adjustment control amount, P n-1 Indicates the demand control quantity of the previous sampling period; The operating power of the temperature control system is adjusted according to the demand control amount.

[0045] In addition, in this embodiment, when the actual temperature is lower than or close to the target temperature, it is determined whether to shut down in combination with whether there is a vehicle charging at present, without waiting for the PID controller to shut down. When the actual temperature is lower than or close to the target temperature, it means that the control has basically achieved the target. If there is no vehicle charging at this time, it means that no more heat will be generated and the control can be shut down. If there is still a vehicle charging at this time, it means that heat will be generated and it needs to be maintained.

[0046] In this embodiment, the target temperature may be a temperature range or an exact temperature value.

[0047] Please refer to Figure 2 , Embodiment 2 of the present invention is: A device 1 for controlling the operating temperature of a power cabinet comprises a processor 2, a memory 3, and an ARM program stored in the memory 3 and executable on the processor 2. When the processor 2 executes the ARM program, the steps in the method for controlling the operating temperature of a power cabinet described in the first embodiment are implemented.

[0048] In summary, the present invention provides a method and device for controlling the working temperature of a power cabinet, which periodically collects ambient temperature and temperature of a temperature zone, and uses the data of the most recent period and an incremental PID controller model to calculate the adjustment control quantity, thereby adjusting the operating power of the temperature control system in real time, achieving better temperature control effects, and reducing power consumption. Fuzzy adaptive tuning parameters are introduced into the incremental PID controller model to effectively suppress the influence of equipment usage time, environmental interference, etc., and achieve better temperature control effects.

[0049] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A control method for a power cabinet temperature control system, characterized in that: Includes steps: S1. According to the pre-divided temperature zones, operating parameters are collected respectively according to the preset sampling period, wherein the operating parameters include the ambient temperature, the power of the temperature control system and the temperature of the temperature zone; S2, constructing an incremental PID controller model, and calculating the adjustment control amount in combination with the operating parameters collected at the latest preset number of times; The preset number of times is 3 times, and the incremental PID controller model is expressed as follows: ΔP=A*e n +B*e n-1 +C*e n-2 ; A=K P (1+T / T i +T d / T); B=-K P (1+2T d / T); C=K P *T d / T; Among them, A, B and C represent control constants, e n 、e n-1 and e n-2 Indicates the deviation signal within the last three sampling cycles. The deviation signal is the difference between the temperature in the temperature zone and the preset target temperature. K P represents the fuzzy adaptive tuning parameter, T i Indicates the integral coefficient, T d represents the differential coefficient; S3, adjusting the operating power of the temperature control system according to the adjustment control amount; When the temperature of the temperature zone is lower than the target temperature or is within a preset range of the target temperature, it is determined whether the vehicle is being charged, and if so, the temperature control system is maintained, otherwise, the temperature control system is shut down.

2. The control method of a power cabinet temperature control system according to claim 1, characterized in that: The determination of the adaptive setting parameters is specifically as follows: With the current deviation signal e n and the deviation change △e as input, which is calculated by fuzzy adaptive tuning according to the preset fine-tuning value table; Where △e=e n -e n-1 ; According to the difference between the ambient temperature and the preset target temperature, the proportionality coefficient of the adaptive setting parameter after adjustment is determined, and the adaptive setting parameter is adjusted according to the proportionality coefficient.

3. The control method of a power cabinet temperature control system according to claim 1, characterized in that: Step S3 is specifically as follows: Calculate the current demand control quantity P according to the adjustment control quantity n : P n =ΔP+P n-1 ; Among them, ΔP represents the adjustment control amount, P n-1 Indicates the demand control quantity of the previous sampling period; The operating power of the temperature control system is adjusted according to the demand control amount.

4. The control method of a power cabinet temperature control system according to claim 1, characterized in that: The steps between step S1 and step S2 also include the following steps: Determine whether the temperature of the temperature zone is less than the preset target temperature. If so, determine whether there is vehicle charging. If there is no vehicle charging, shut down the temperature control system without waiting for the command of the PID controller, otherwise enter step S2.

5. The control method of a power cabinet temperature control system according to claim 1, characterized in that: Integration coefficient T i The value range is [240,480], and the differential coefficient T d The value range is [3,150].

6. A control terminal of a power cabinet temperature control system, comprising a processor, a memory, and an ARM program stored in the memory and executable on the processor, characterized in that: When the processor executes the ARM program, the following steps are implemented: S1. According to the pre-divided temperature zones, operating parameters are collected respectively according to the preset sampling period, wherein the operating parameters include the ambient temperature, the power of the temperature control system and the temperature of the temperature zone; S2, constructing an incremental PID controller model, and calculating the adjustment control amount in combination with the operating parameters collected at the latest preset number of times; The preset number of times is 3 times, and the incremental PID controller model is expressed as follows: ΔP=A*e n +B*e n-1 +C*e n-2 ; A=K P (1+T / T i +T d / T); B=-K P (1+2T d / T); C=K P *T d / T; Among them, A, B and C represent control constants, e n 、e n-1 and e n-2 Indicates the deviation signal within the last three sampling cycles. The deviation signal is the difference between the temperature in the temperature zone and the preset target temperature. K P represents the fuzzy adaptive tuning parameter, T i Indicates the integral coefficient, T d represents the differential coefficient; S3, adjusting the operating power of the temperature control system according to the adjustment control amount; When the temperature of the temperature zone is lower than the target temperature or is within a preset range of the target temperature, it is determined whether the vehicle is being charged, and if so, the temperature control system is maintained, otherwise, the temperature control system is shut down.

7. The control terminal of the power cabinet temperature control system according to claim 6, characterized in that: The determination of the adaptive setting parameters is specifically as follows: With the current deviation signal e n and the deviation change △e as input, which is calculated by fuzzy adaptive tuning according to the preset fine-tuning value table; Where △e=e n -e n-1 ; According to the difference between the ambient temperature and the preset target temperature, the proportionality coefficient of the adaptive setting parameter after adjustment is determined, and the adaptive setting parameter is adjusted according to the proportionality coefficient.

8. The control terminal of the power cabinet temperature control system according to claim 6, characterized in that: Step S3 is specifically as follows: Calculate the current demand control quantity P according to the adjustment control quantity n : P n =ΔP+P n-1 ; Among them, ΔP represents the adjustment control amount, P n-1 Indicates the demand control quantity of the previous sampling period; The operating power of the temperature control system is adjusted according to the demand control amount.

9. The control terminal of the power cabinet temperature control system according to claim 6, characterized in that: The steps between step S1 and step S2 also include the following steps: Determine whether the temperature of the temperature zone is less than the preset target temperature. If so, determine whether there is vehicle charging. If there is no vehicle charging, shut down the temperature control system without waiting for the command of the PID controller, otherwise enter step S2.

10. The control terminal of the power cabinet temperature control system according to claim 6, characterized in that: Integration coefficient T i The value range is [240,480], and the differential coefficient T d The value range is [3,150].

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