Fuzzy control method, system and equipment for liquid cooling machine and storage medium

Abstract

The invention belongs to the technical field of liquid cooling machines, and discloses a liquid cooling machine fuzzy control method, system and device and a storage medium. The liquid cooling machine fuzzy control method comprises the steps that the oil inlet temperature and the oil outlet temperature of a liquid cooling machine serve as input variables, the cooling fan rotating speed adjustment rate and the liquid cooling oil flow speed adjustment rate serve as output variables, and the membership degree and fuzzy control rules of fuzzy variables are determined; the fuzzy control rule carries out fuzzy reasoning on the rotation speed adjustment rate of the heat dissipation fan and the flow speed adjustment rate of the liquid cooling oil, the oil inlet temperature and the oil outlet temperature of the liquid cooling machine are controlled so as to reduce the oil inlet temperature and the oil outlet temperature of the liquid cooling machine, the oil inlet temperature and the oil outlet temperature are collected in real time in combination with a sensor, and the temperature of the oil inlet and the temperature of the oil outlet are calculated. The liquid cooling pump and the cooling fan are adjusted in real time, so that the working temperature of the gun line is always in a proper working range, the whole operation process is always efficient and stable, and the technical problem of derated output caused by heating of a high-power charging gun line during current transmission is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of liquid coolers and relates to a fuzzy control method, system, equipment and storage medium for a liquid cooler. Background Art

[0002] The energy storage system is a system for storing and releasing electrical energy. Its core components include battery packs / battery groups (collectively referred to as batteries). The batteries in the energy storage system will generate a lot of heat during the charging and discharging process. If the heat cannot be discharged in time, the temperature of the energy storage system will rise, posing a safety hazard, and further affecting the performance of the battery and the normal operation of the energy storage system. The high-power charging gun line will generate severe heat when transmitting a charging current of more than 500-800A, resulting in a derating of the output. Summary of the invention

[0003] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a fuzzy control method, system, device and storage medium for a liquid cooler. Through the fuzzy control algorithm, combined with the sensor, the inlet and outlet liquid temperatures are collected in real time, and the liquid cooler pump and fan are adjusted in real time, so that the working temperature of the gun line is always within the appropriate working range, ensuring that the charging pile always operates efficiently and stably during the entire operation process.

[0004] In order to achieve the above object, the present invention adopts the following technical solution: The present invention provides a fuzzy control method for a liquid cooler, comprising the following steps: taking the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler as input variables, and taking the speed adjustment rate of the cooling fan as the input variable. and liquid cooling oil flow rate adjustment rate As the output variable, a triangular fuzzy membership function and a fuzzy control rule are determined; the fuzzy control rule adjusts the speed of the cooling fan and liquid cooling oil flow rate adjustment rate Fuzzy reasoning is performed to control the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler to reduce the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler. Furthermore, the determination of the membership degree also includes confirming fuzzy variables, which are related to the oil inlet temperature FI, the oil outlet temperature SP, the cooling fan speed adjustment rate, and the like. and liquid cooling oil flow rate adjustment rate Provide fuzzy language description.

[0005] Furthermore, the oil inlet temperature FI is

[0006] in, is the maximum temperature that the oil inlet can accept. is the oil inlet temperature value collected by the sensor at the i-th moment, It is the minimum acceptable temperature of the oil inlet. Furthermore, the oil outlet temperature SP is

[0007] in, is the maximum temperature value that the oil outlet can accept. is the oil outlet temperature value collected by the sensor at the i-th moment, It is the lowest temperature value that the oil outlet can accept.

[0008] Furthermore, the fuzzy language of the oil inlet temperature FI is , the characters are , the value range is ; The fuzzy language of the oil outlet temperature SP is , the characters are , the value range is ; The cooling fan speed adjustment rate and liquid cooling oil flow rate adjustment rate The fuzzy language is , the characters are , the cooling fan speed adjustment rate The value range is , Liquid cooling oil flow rate adjustment rate The value range is .

[0009] Furthermore, the triangle fuzzy membership function is

[0010] Among them, a, b, and c are the three vertices of the defined triangle, b is the center point of the triangle, a is the left vertex of the triangle, and c is the right vertex of the triangle.

[0011] Furthermore, the fuzzy control rule adjusts the speed of the cooling fan and liquid cooling oil flow rate adjustment rate After fuzzy reasoning, it also includes defuzzification and cooling fan speed adjustment rate The real value of is and liquid cooling oil flow rate adjustment rate The real value of is ;

[0012]

[0013] in, is the membership value, Cooling fan speed adjustment rate The fuzzy value of Liquid cooling oil flow rate adjustment rate The fuzzy value of .

[0014] The present invention also provides a fuzzy control system for a liquid cooler, comprising: a confirmation module for taking the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler as input variables and the cooling fan speed adjustment rate and liquid cooling oil flow rate adjustment rate The output variable is used to determine the membership degree of the fuzzy variable and the fuzzy control rule; the control module is used for the fuzzy control rule to adjust the speed of the cooling fan and liquid cooling oil flow rate adjustment rate Fuzzy reasoning is performed to control the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler to reduce the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler.

[0015] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned liquid cooler fuzzy control method when executing the computer program.

[0016] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned liquid cooler fuzzy control method are implemented.

[0017] Compared with the prior art, the present invention has the following beneficial technical effects: The present invention provides a fuzzy control method for a liquid cooler, wherein the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler are input variables, and the speed adjustment rate of the cooling fan is and liquid cooling oil flow rate adjustment rate The oil inlet and outlet temperatures of the liquid cooler are lowered through fuzzy control. When the oil inlet temperature is high or the ambient temperature is high, the fan speed is increased to enhance the heat dissipation effect; otherwise, the speed is reduced to reduce noise and energy consumption. Through real-time monitoring and precise adjustment, the liquid cooling oil flow rate and the cooling fan speed are adjusted in real time and accurately, thereby ensuring that the working temperature of the gun line is always within the appropriate working range.

[0018] The present invention discloses a fuzzy control method for a liquid cooler, which improves charging efficiency and ensures that the gun line operates within a suitable operating temperature range by adjusting the working states of a liquid cooler pump and a cooling fan in real time, thereby improving charging efficiency and charging speed; prolonging the life of equipment: effective temperature control and heat dissipation measures can reduce the risk of equipment damage due to overheating, and prolong the service life of a charging pile and its key components; and improving user experience: a stable charging process, a fast charging speed and reliable safety guarantees can improve user satisfaction and trust in the charging pile, thereby attracting more users to charge. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a principle block diagram of a fuzzy control method for a liquid cooler of the present invention; Figure 2 It is a triangular membership function setting diagram of the oil inlet temperature FI in an embodiment of the present invention; Figure 3 It is a triangular membership function setting diagram of the oil outlet temperature SP in an embodiment of the present invention; Figure 4 is the speed adjustment rate of the cooling fan in the embodiment of the present invention Triangular membership function setting diagram; Figure 5 is the liquid cooling oil flow rate adjustment rate in the embodiment of the present invention Triangular membership function setting diagram; Figure 6 This is a diagram for setting the fuzzy control rule program in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0021] Example 1 The present invention provides a fuzzy control method for a liquid cooling machine, such as Figure 1 As shown, it includes: taking the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler as input variables, and taking the cooling fan speed adjustment rate and liquid cooling oil flow rate adjustment rate The fuzzy variable membership and fuzzy control rules are determined as output variables; the fuzzy control rules are used to adjust the speed of the cooling fan. and liquid cooling oil flow rate adjustment rate Perform fuzzy inference to control the inlet temperature FI and the outlet temperature SP of the liquid chiller, so as to reduce the inlet temperature FI and the outlet temperature SP of the liquid chiller. Specifically, first determine the input variables and output variables. Select the inlet temperature FI and the outlet temperature SP as the input variables. The calculation formula for the inlet temperature FI is as follows

[0022] where, is the maximum temperature value that the inlet can accept. In this embodiment, the maximum temperature value that the inlet can accept is 85 °C. is the inlet temperature value collected by the sensor at the i-th moment. is the minimum temperature value that the inlet can accept. The minimum temperature value that the inlet can accept is 15 °C.

[0023] The calculation formula for the outlet temperature SP is as follows

[0024] where, is the maximum temperature value that the outlet can accept. In this embodiment, the maximum temperature value that the outlet can accept is 65 °C. is the outlet temperature value collected by the sensor at the i-th moment. is the minimum temperature value that the outlet can accept. The minimum temperature value that the outlet can accept is 15 °C.

[0025] After that, use fuzzy variables to describe the input variables and output variables. The fuzzy language for the inlet temperature FI is , the character is , and the value range is . The feedback value of the inlet temperature "Jin Yi" is 15 - 40 °C, and the character represents the value range as . For every 1 °C increase in the feedback value temperature, the value range increases by 0.02; the feedback value of the inlet temperature "Jin Er" is 41 - 65 °C, and the character represents the value range as . For every 1 °C increase in the feedback value temperature, the value range increases by 1 / 60; the feedback value of the inlet temperature "Jin San" is 66 - 85 °C, and the character represents the value range as . For every 1 °C increase in the feedback value temperature, the value range increases by 3 / 190.

[0026] The fuzzy language for the outlet temperature SP is , the character is , and the value range is . The feedback value of the outlet temperature "Chu Yi" is 15 - 30 °C, and the character represents the value range as , the feedback value temperature increases by 1°C, the value range increases by 0.02; the feedback value of the oil outlet temperature "out 2" is 31-49°C, and the characters indicate the value range is , the feedback value temperature increases by 1°C, the value range increases by 1 / 45; the feedback value of the oil inlet temperature "out of three" is 50-65°C, and the characters indicate the value range is , the feedback value range increases by 0.02 for every 1°C increase in temperature.

[0027] The cooling fan speed adjustment rate and liquid cooling oil flow rate adjustment rate The fuzzy language is , the characters are , the cooling fan speed adjustment rate The value range is , Liquid cooling oil flow rate adjustment rate The value range is . Cooling fan speed adjustment rate The setting value is In this embodiment The setting value is 0.25, the liquid cooling oil flow rate adjustment rate The setting value is In this embodiment The setting value is 0.25; the cooling fan speed adjustment rate The setting value is In this embodiment The setting value is 0.42, and the liquid cooling oil flow rate adjustment rate The setting value is In this embodiment The setting value is 0.42; the cooling fan speed adjustment rate The setting value is In this embodiment The setting value is 0.59, the liquid cooling oil flow rate adjustment rate The setting value is In this embodiment The setting value is 0.59; the cooling fan speed adjustment rate The setting value is In this embodiment The setting value is 0.79, the liquid cooling oil flow rate adjustment rate The setting value is In this embodiment The setting value is 0.79; the cooling fan speed adjustment rate The setting value is In this embodiment The setting value is 0.92, the liquid cooling oil flow rate adjustment rate The setting value is In this embodiment The setting value is 0.92, the cooling fan speed adjustment rate Described in character language , Liquid cooling oil flow rate adjustment rate Described in character language .

[0028] After that, the membership of the fuzzy variables is determined, and the triangular membership function of the oil inlet temperature FI is as follows: Figure 2 As shown, the triangular membership function of the oil outlet temperature SP is as follows Figure 3 As shown, the cooling fan speed adjustment rate The triangular membership function is Figure 4 As shown, the liquid cooling oil flow rate adjustment rate The triangular membership function is Figure 5 As shown, the fuzzy membership functions of all variables are symmetrical triangular membership functions, and the formula is

[0029] Among them, a, b, and c are the three vertices of the defined triangle, b is the center point of the triangle, a is the left vertex of the triangle, and c is the right vertex of the triangle. The distance between a and c determines the width of the triangle, and the position of b determines the height of the triangle.

[0030] Then the fuzzy control rules are established, and the speed adjustment rate of the cooling fan and liquid cooling oil flow rate adjustment rate The control rules are shown in Table 1, and the fuzzy control rule program settings are as follows Figure 6 shown.

[0031] Table 1 and Control rules

[0032] Cooling fan speed adjustment rate and liquid cooling oil flow rate adjustment rate The control rules are converted into actual values ​​as shown in Table 2 Table 2 and Control rules (values)

[0033] After that, perform fuzzy reasoning, let FI be A, SP be B, if IFFI is A and SP is B, THEN Pc is C andPm is D, where , , , .

[0034] Using Mamdani operation to find fuzzy implication relationship and ,Mamdani operation can obtain accurate control instructions through fuzzy reasoning based on the fuzzy information of the input variables and ,achieve stable control of the system.

[0035]

[0036]

[0037] Calculate using intersection operation ,

[0038] in, is a composition operator, , The result of the intersection operation is recorded as

[0039] The vector form of

[0040]

[0041]

[0042] in, and are all matrices with 9 rows and 5 columns. for .

[0043] Assume FI is and SP is , then according to fuzzy reasoning,

[0044]

[0045] Specifically, the oil inlet temperature detection value is 53, and the fuzzy language variable is "medium". After FI is converted into language, it can be described as The oil outlet temperature detection value is 40, and the fuzzy language variable is "medium". After FI language conversion, it can be described as , based on fuzzy reasoning, we can infer that "IFFI is 0.5 and SP is 0.5, THEN Pc is 0.59 and Pm is 0.59".

[0046] After defuzzification, the output variable is defuzzified by weighted average method. The weighted average method converts the fuzzy output into a clear output by taking the weighted average of the fuzzy output and the corresponding weight. The calculation is as follows:

[0047]

[0048] in, Cooling fan speed adjustment rate The real value of Liquid cooling oil flow rate adjustment rate The real value of is the membership value, Cooling fan speed adjustment rate The fuzzy value can also be understood as the reflection value of the triangular fuzzy membership function, that is, the weight value. Different factors and rules are given different weights to oppose their relative importance, so as to better reflect the actual meaning and value of the fuzzy output. Liquid cooling oil flow rate adjustment rate The fuzzy value of charging power is 0.3, the charging time is 0.1, the ambient temperature is 0.1, the inlet temperature is 0.4, and the outlet temperature is 0.3. When it is 0.59, substitute and The value obtained is 0.708, that is, the real value of the cooling fan speed adjustment rate and the liquid cooling oil flow rate adjustment rate is 70.8%.

[0049] Example 2 The present invention discloses a fuzzy control system for a liquid cooler, comprising a confirmation module and a control module, wherein the confirmation module is used to use the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler as input variables and the cooling fan speed adjustment rate as the cooling fan speed adjustment rate. and liquid cooling oil flow rate adjustment rate The output variable is used to determine the membership degree of the fuzzy variable and the fuzzy control rule; the control module is used for the fuzzy control rule to adjust the speed of the cooling fan and liquid cooling oil flow rate adjustment rate Fuzzy reasoning is performed to control the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler to reduce the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler.

[0050] Example 3 The present invention provides a terminal device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the fuzzy control method of the liquid cooler, including the following steps: taking the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler as input variables, and taking the speed adjustment rate of the cooling fan as the input variable. and liquid cooling oil flow rate adjustment rate The fuzzy variable membership and fuzzy control rules are determined as output variables; the fuzzy control rules are used to adjust the speed of the cooling fan. and liquid cooling oil flow rate adjustment rate Fuzzy reasoning is performed to control the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler to reduce the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler.

[0051] Example 4 The present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0052] The processor may load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the fuzzy control method for the liquid cooler in the above embodiment; the processor may load and execute the following steps: taking the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler as input variables, taking the speed adjustment rate of the cooling fan as input variables, and and liquid cooling oil flow rate adjustment rate The fuzzy variable membership and fuzzy control rules are determined as output variables; the fuzzy control rules are used to adjust the speed of the cooling fan. and liquid cooling oil flow rate adjustment rate Fuzzy reasoning is performed to control the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler to reduce the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler.

[0053] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0054] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0055] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0056] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A fuzzy control method for a liquid cooler, characterized in that: The following steps are involved: The oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler are used as input variables, and the cooling fan speed adjustment rate is used as and liquid cooling oil flow rate adjustment rate As output variables, determine the triangle fuzzy membership function and fuzzy control rules; The fuzzy control rule adjusts the speed of the cooling fan and liquid cooling oil flow rate adjustment rate Fuzzy reasoning is performed to control the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler to reduce the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler.

2. The fuzzy control method for a liquid cooling machine according to claim 1, characterized in that: The determination of the membership degree also includes confirming the fuzzy variables, and the fuzzy variables have an influence on the oil inlet temperature FI, the oil outlet temperature SP, the cooling fan speed adjustment rate and liquid cooling oil flow rate adjustment rate Provide fuzzy language description.

3. The fuzzy control method for a liquid cooler according to claim 1, characterized in that: The oil inlet temperature FI is in, is the maximum temperature value that the oil inlet can accept, is the oil inlet temperature value collected by the sensor at the i-th moment, It is the minimum acceptable temperature of the oil inlet.

4. The fuzzy control method for a liquid cooler according to claim 1, characterized in that: The oil outlet temperature SP is in, is the maximum temperature value that the oil outlet can accept. is the oil outlet temperature value collected by the sensor at the i-th moment, It is the lowest temperature value that the oil outlet can accept.

5. The fuzzy control method for a liquid cooling machine according to claim 2, characterized in that: The fuzzy language of the oil inlet temperature FI is: , the characters are , the value range is ; The fuzzy language of the oil outlet temperature SP is: , the characters are , the value range is ; The cooling fan speed adjustment rate and liquid cooling oil flow rate adjustment rate The fuzzy language is , the characters are , the cooling fan speed adjustment rate The value range is , Liquid cooling oil flow rate adjustment rate The value range is .

6. The fuzzy control method for a liquid cooler according to claim 1, characterized in that: The triangle fuzzy membership function is: Among them, a, b, and c are the three vertices of the defined triangle, b is the center point of the triangle, a is the left vertex of the triangle, and c is the right vertex of the triangle.

7. The fuzzy control method for a liquid cooling machine according to claim 1, characterized in that: The fuzzy control rule adjusts the speed of the cooling fan and liquid cooling oil flow rate adjustment rate After fuzzy reasoning, it also includes defuzzification and cooling fan speed adjustment rate The real value of is and liquid cooling oil flow rate adjustment rate The real value of is ; in, is the membership value, Cooling fan speed adjustment rate The fuzzy value of Liquid cooling oil flow rate adjustment rate The fuzzy value of .

8. A fuzzy control system for a liquid cooler, characterized in that: include: The confirmation module is used to use the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler as input variables and the cooling fan speed adjustment rate and liquid cooling oil flow rate adjustment rate For output variables, determine the membership degree of fuzzy variables and fuzzy control rules; A control module is used for adjusting the speed of the cooling fan according to the fuzzy control rule. and liquid cooling oil flow rate adjustment rate Fuzzy reasoning is performed to control the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler to reduce the oil inlet temperature FI and the oil outlet temperature SP of the liquid cooler.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the fuzzy control method for a liquid cooler according to any one of claims 1 to 7 are implemented.

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

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