Method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change material and storage medium

Abstract

The invention discloses a method for simultaneously measuring the specific heat capacity and the surface heat flux density of a solid-liquid phase change material and a storage medium. The method comprises the following steps: S1, establishing an internal coupling heat transfer model of the solid-liquid phase change material; s2, laser is used for heating the surface of the solid-liquid phase change material to measure the temperature; s3, solving a transient heat transfer model; s4, establishing input signals em, n and a particle individual fitness function Fl for simultaneously measuring the specific heat capacity and the surface heat flux density of the solid-liquid phase change material; s5, constructing a hybrid optimization module; s6, the specific heat capacity and the surface heat flux density of the solid-liquid phase change material are updated; s7, checking whether an iteration stop condition is reached or not; and S8, recording the specific heat capacity and the surface heat flux density of the new solid-liquid phase change material at the moment, and outputting as a measurement result. The storage medium is used for storing a computer program for executing the method. The method has the advantages of simple principle, simplicity and convenience in operation, high error interference resistance and the like.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of material property detection, and in particular to a method and a storage medium for simultaneously measuring the specific heat capacity and surface heat flux density of a solid-liquid phase change material. Background Art

[0002] As a green, clean and renewable energy, solar energy is one of the important options for mankind to cope with energy shortages, climate change and energy conservation and emission reduction.

[0003] In the utilization of solar energy, the timeliness and regional differences of light are inevitable. Using solid-liquid phase change materials for heat storage and energy storage can effectively solve the contradiction between the mismatch between solar energy supply and demand in time and space, and is one of the important ways to improve the utilization of new energy.

[0004] In the technology of using solid-liquid phase change materials, the specific heat capacity and surface heat flux density of solid-liquid phase change materials are the basic parameters for the design and optimization of thermal energy storage systems, and their accurate measurement is of great significance for promoting the utilization of solar energy. The traditional measurement of the specific heat capacity or surface heat flux density of solid-liquid phase change materials is a direct measurement method. This measurement method is highly sensitive to measurement errors, and random errors have a great impact on the measurement results. In addition, it can only measure one of the parameters of specific heat capacity or surface heat flux density, and cannot achieve simultaneous measurement of the above two parameters, so the measurement efficiency is very low. Summary of the invention

[0005] The technical problem to be solved by the present invention is: in view of the technical problems existing in the prior art, the present invention provides a method and storage medium for simultaneously measuring the specific heat capacity and surface heat flux density of solid-liquid phase change materials with simple principle, easy operation and strong anti-error interference ability.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] A method for simultaneously measuring specific heat capacity and surface heat flux density of a solid-liquid phase change material, comprising:

[0008] Step S1: Randomly initialize the position of each particle and give an initial guess of the surface heat flux density of the solid-liquid phase change material. Establish a solid-liquid phase change material internal coupling heat transfer model and set the current iteration number to k = 0;

[0009] Step S2: Use laser to heat the surface of the solid-liquid phase change material, select M sampling points on the surface of the solid-liquid phase change material, and use an infrared thermal imager to measure the temperature of the M sampling points at N measurement times.

[0010] Step S3: Based on the specific heat capacity c of the solid-liquid phase change material k and surface heat flux Solve the transient heat transfer model and numerically calculate the temperature of M measuring points at N measuring times

[0011] Step S4: Based on the temperature measurement values ​​of M measuring points and calculated values Establish the input signal e for simultaneous measurement of specific heat capacity and surface heat flux density of solid-liquid phase change materials m,n and the particle individual fitness function F l ;

[0012] Step S5: Construct a hybrid optimization module for simultaneous measurement of specific heat capacity and surface heat flux density of solid-liquid phase change materials. m,n and numerically calculated temperature Perform numerical optimization;

[0013] Step S6: updating the specific heat capacity and surface heat flux density of the solid-liquid phase change material according to the optimization result;

[0014] Step S7: Check whether the iteration stop condition has been met. If the stop condition is met, proceed to step S8 and return to step S3 to continue iterative update;

[0015] Step S8: Record the specific heat capacity and surface heat flux density of the new solid-liquid phase change material at this time, output them as the measurement result, and end the measurement.

[0016] As a further improvement of the method of the present invention: the random initialization of each individual particle position in step S1 refers to randomly generating the position of each individual particle in the solution space, and using each individual particle position to represent a possible value of specific heat capacity, and the initialization position is generated according to the following formula:

[0017]

[0018] Where R is a random number uniformly distributed in the interval [0,1], l is the lth particle individual, NL is the number of individuals in the particle group, the superscript 0 indicates the 0th iteration, i.e. initialization, and X max is the maximum value of the specific heat capacity of the solid-liquid phase change material, X min It is the minimum value of the specific heat capacity of solid-liquid phase change material.

[0019] As a further improvement of the method of the present invention: in the step S1, the initial guess value of the surface heat flux density is a given starting value of the measurement based on the external heat source characteristics of the solid-liquid phase transition material, and the initial value of the surface heat flux density is set to C is a fixed positive number, NI is the number of reconstruction positions, and NJ is the number of reconstruction moments.

[0020] As a further improvement of the method of the present invention: in the step S1, the internal heat transfer model of the solid-liquid phase change material includes two heat transfer modes: internal heat conduction and radiation of the solid-liquid phase change material; the heat transfer process is described by the following energy equation:

[0021]

[0022] Where ρ, c and λ represent density, specific heat capacity and thermal conductivity respectively, T and t represent temperature and time respectively. and f l denote the latent heat of phase change and the liquid fraction, respectively. Represents the divergence of the heat flux density of radiation heat transfer, which is obtained according to the following formula:

[0023]

[0024] Where Ω represents the direction of light transmission, r represents the spatial position, κ represents the absorption coefficient, and I represents the radiation intensity, which is obtained by solving the following radiation transfer equation:

[0025]

[0026] Among them, Ω′ represents the direction of external incident light, β and σ s represent the attenuation coefficient and scattering coefficient respectively, and Φ represents the scattering phase function.

[0027] As a further improvement of the method of the present invention: the selection of M sampling points on the surface of the solid-liquid phase change material in step S2 is based on the measurement requirements of the surface heat flux density, and M temperature measurement points that are consistent with the simultaneous measurement positions of the surface heat flux density are selected on the surface of the solid-liquid phase change material.

[0028] As a further improvement of the method of the present invention: the numerical calculation of the temperature of M measuring points at N measuring times in step S3 is It refers to the calculation obtained by solving the energy equation and the radiation transfer equation. The present invention uses the finite volume method to solve the energy equation and the radiation transfer equation to obtain it.

[0029] As a further improvement of the method of the present invention: the input signal e in step S4 m,n and the particle individual fitness function F l , established as follows:

[0030]

[0031]

[0032] As a further improvement of the method of the present invention: the hybrid optimization module in step S5 includes a particle swarm optimization module and a fuzzy reasoning module; the particle swarm optimization module performs group position optimization through NL particle individuals, and uses the position of each particle individual to represent a potential specific heat capacity measurement value; the moving speed and position of the particle individual in each iteration process are updated according to the following formula:

[0033]

[0034]

[0035] Among them, the superscript k1 is the number of inner loop iterations of the particle swarm optimization module, ω is the speed iteration weight factor, V is the individual particle moving speed, c1 and c2 are acceleration coefficients, r1 and r2 are random numbers uniformly distributed in the interval [0,1], P l is the position that the lth particle has searched so far to minimize the objective function, P g The position that minimizes the objective function found by the entire particle group so far.

[0036] As a further improvement of the method of the present invention: the specific heat capacity c of the solid-liquid phase change material updated in step S6 k and surface heat flux It is updated according to the following formula:

[0037]

[0038]

[0039] The iteration stop condition refers to the following two conditions being met at the same time:

[0040]

[0041]

[0042] Among them, ε1 and ε2 are two specified small positive numbers.

[0043] The present invention further provides a storage medium, which can be read by a computer or a processor and stores a computer program for executing the above method.

[0044] Compared with the prior art, the advantages of the present invention are:

[0045] 1. The method and storage medium for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials of the present invention have simple principles and are easy to operate. The specific heat capacity and surface heat flux density can be measured simultaneously by solving the inverse heat transfer problem. The entire method has strong error resistance and can solve the problem of accurate simultaneous measurement of multiple parameters.

[0046] 2. The method and storage medium for simultaneously measuring the specific heat capacity and surface heat flux density of solid-liquid phase change materials of the present invention, the method uses laser to heat the solid-liquid phase change material, and uses the hybrid optimization module established by the present invention to reconstruct the specific heat capacity and surface heat flux density of the solid-liquid phase change material. The method has no restrictions on the shape, size, type, etc. of the solid-liquid phase change material, and can simultaneously measure the specific heat capacity and surface heat flux density of the solid-liquid phase change material, which is of great significance for promoting the utilization of solar energy storage and has strong engineering practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is the fuzzy subset A in the specific application example l The membership function curve of .

[0048] Figure 2 In a specific application example, the fuzzy subset B l The membership function curve of .

[0049] Figure 3 It is a schematic diagram of the process of simultaneously measuring the specific heat capacity and surface heat flux density of solid-liquid phase change materials in a specific application example.

[0050] Figure 4 It is a schematic diagram of the true value of the surface heat flux density of the solid-liquid phase change material in a specific application example.

[0051] Figure 5 It is a schematic diagram of the surface heat flux density measurement results of solid-liquid phase change materials in a specific application example.

[0052] Figure 6 It is a schematic diagram of the measurement error distribution of the surface heat flux density of solid-liquid phase change materials in a specific application example. DETAILED DESCRIPTION

[0053] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] The present invention discloses a method for simultaneously measuring the specific heat capacity and surface heat flux density of a solid-liquid phase change material. The method utilizes a laser to heat the surface of the solid-liquid phase change material, utilizes an infrared thermal imager to measure the temperature of the material surface, and reconstructs the specific heat capacity and surface heat flux density of the phase change material according to a hybrid optimization module established by the present invention. The important innovation of the present invention is that through a hybrid optimization module, the temperature information on the surface of the material that is easy to measure is utilized to simultaneously reconstruct the specific heat capacity and surface heat flux density of the solid-liquid phase change material, and finally provides an effective technical solution for the simultaneous measurement of multiple parameters of solid-liquid phase change materials.

[0055] like Figure 3 As shown, the method for simultaneously measuring the specific heat capacity and surface heat flux density of a solid-liquid phase change material of the present invention comprises:

[0056] Step S1: Randomly initialize the position of each particle and give an initial guess of the surface heat flux density of the solid-liquid phase change material. Establish a solid-liquid phase change material internal coupling heat transfer model and set the current iteration number to k = 0;

[0057] Step S2: Use laser to heat the surface of the solid-liquid phase change material, select M sampling points on the surface of the solid-liquid phase change material, and use an infrared thermal imager to measure the temperature of the M sampling points at N measurement times.

[0058]

[0059] Step S3: Based on the specific heat capacity c of the solid-liquid phase change material k and surface heat flux Solve the transient heat transfer model and numerically calculate the temperature of M measuring points at N measuring times

[0060] Step S4: Based on the temperature measurement values ​​of M measuring points and calculated values Establish the input signal e for simultaneous measurement of specific heat capacity and surface heat flux density of solid-liquid phase change materials m,n (m=1,2,…,M;n=1,2,…,N) and the fitness function of individual particles F l (l=1,2,…,NL);

[0061] Step S5: Construct a hybrid optimization module for simultaneous measurement of specific heat capacity and surface heat flux density of solid-liquid phase change materials. m,n (m=1,2,…,M;n=1,2,…,N) and numerically calculated temperature Perform numerical optimization;

[0062] Step S6: Update the specific heat capacity c of the solid-liquid phase change material according to the optimization result k and surface heat flux

[0063]

[0064] Step S7: Check whether the iteration stop condition has been met. If the stop condition is met, proceed to step S8 and return to step S3 to continue iterative update;

[0065] Step S8: Record the specific heat capacity and surface heat flux density of the new solid-liquid phase change material at this time, output them as the measurement result, and end the measurement.

[0066] In a specific application example, the random initialization of each individual particle position in step S1 refers to randomly generating the position of each individual particle in the solution space, and using each individual particle position to represent a possible value of specific heat capacity, and the initialization position is generated according to the following formula:

[0067]

[0068] Where R is a random number uniformly distributed in the interval [0,1], l is the lth particle individual, NL is the number of individuals in the particle group, the superscript 0 indicates the 0th iteration, i.e. initialization, and X max is the maximum value of the specific heat capacity of the solid-liquid phase change material, set to X max =5000J / (kg·K),X min is the minimum value of the specific heat capacity of the solid-liquid phase change material, set to X min =500J / (kg·K).

[0069] As a preferred embodiment, in step S1, the initial guess value of the surface heat flux density is given as the starting value of the measurement according to the external heat source characteristics of the solid-liquid phase transition material, and the initial value of the surface heat flux density is set to C is a fixed positive number, NI is the number of reconstruction positions, and NJ is the number of reconstruction moments.

[0070] As a preferred embodiment, in step S1, the internal heat transfer model of the solid-liquid phase change material includes two heat transfer modes: internal heat conduction and radiation of the solid-liquid phase change material. The heat transfer process is described by the following energy equation:

[0071]

[0072] Where ρ, c and λ represent density, specific heat capacity and thermal conductivity respectively, T and t represent temperature and time respectively. and f l denote the latent heat of phase change and the liquid fraction, respectively. Represents the divergence of the heat flux density of radiation heat transfer, which is obtained according to the following formula:

[0073]

[0074] Where Ω represents the direction of light transmission, r represents the spatial position, κ represents the absorption coefficient, and I represents the radiation intensity, which is obtained by solving the following radiation transfer equation:

[0075]

[0076] Among them, Ω′ represents the direction of external incident light, β and σ s represent the attenuation coefficient and scattering coefficient respectively, and Φ represents the scattering phase function.

[0077] In a specific application example, the step S2 of selecting M sampling points on the surface of the solid-liquid phase change material is based on the measurement requirements of the surface heat flux density, and M temperature measurement points that are consistent with the simultaneous measurement positions of the surface heat flux density are selected on the surface of the solid-liquid phase change material.

[0078] In a specific application example, the numerical calculation of the temperature of M measuring points at N measuring times in step S3 is It is calculated by solving the energy equation and the radiation transfer equation. The present invention uses the finite volume method to solve the energy equation and the radiation transfer equation to obtain

[0079]

[0080] In a specific application example, the input signal e in step S4 is m,n (m=1,2,…,M;n=1,2,…,N) and the fitness function of individual particles F l (l=1,2,…,NL), established as follows:

[0081]

[0082]

[0083] In a specific application example, the hybrid optimization module in step S5 includes a particle swarm optimization module and a fuzzy reasoning module; the particle swarm optimization module performs group position optimization through NL particle individuals, and uses the position of each particle individual to represent a potential specific heat capacity measurement value; the moving speed and position of the particle individual are updated according to the following formula in each iteration:

[0084]

[0085]

[0086] Among them, the superscript k1 is the number of inner loop iterations of the particle swarm optimization module, ω is the speed iteration weight factor, V is the individual particle moving speed, c1 and c2 are acceleration coefficients, r1 and r2 are random numbers uniformly distributed in the interval [0,1], P l is the position that the lth particle has searched so far to minimize the objective function, P g The position that minimizes the objective function found by the entire particle group so far.

[0087] The fuzzy inference module is based on the input signal e m,n (m=1,2,…,M;n=1,2,…,N) to perform fuzzy reasoning and obtain the output signal d m,n(m=1,2,…,M;n=1,2,…,N),to update the surface heat flux density; set the range of input signal and fuzzy inference output signal to [-r i ,r i ] and [-r o ,r o ], the two value ranges are divided into 7 fuzzy subsets, represented by {A1, A2, A3, A4, A5, A6, A7} and {B1, B2, B3, B4, B5, B6, B7}, and the logical values ​​corresponding to the 7 fuzzy subsets are NB (negative large), NM (negative medium), NS (negative small), ZE (zero), PS (positive small), PM (positive medium) and PB (positive large); the isosceles triangle membership function is used to determine the fuzzy input set A l (l=1,2,3,…,7) and fuzzy output set B l The membership degree of (l=1,2,3,…,7) is as follows Figure 1 and Figure 2 As shown, by the fuzzy subset A l To fuzzy subset B l The fuzzy inference rules are shown in Table 1.

[0088] Table 1 Fuzzy reasoning rules

[0089] enter NB NM NS ZE PS PM PB Output PB PM PS ZE NS NM NB

[0090] As a preferred embodiment, according to the fuzzy inference output, the surface heat flux density is updated according to the following formula:

[0091]

[0092] Among them, k2 is the number of loop iterations in the fuzzy reasoning module, α m,n,i,j is the temperature T at the mth measuring point and the nth measuring moment m,n For the i-th measurement position and j-th measurement time, the heat flux q i,j The weighting factor is calculated according to the following formula:

[0093]

[0094] in, is the heat flux q at the i-th measurement position and j-th measurement time i,j For the mth measuring point, the temperature T at the nth measuring time m,n sensitivity.

[0095] In a specific application example, the specific heat capacity c of the solid-liquid phase change material updated in step S6 is k and surface heat flux It is updated according to the following formula:

[0096]

[0097]

[0098] In a specific application example, the iteration stop condition in step S6 refers to the following two conditions being satisfied at the same time:

[0099]

[0100]

[0101] Among them, ε1 and ε2 are two specified small positive numbers, and the value of ε1 is 10 -3 , ε2=10 -6 .

[0102] In a specific application example, the density of the solid-liquid phase change material is set to ρ = 905 kg / m 3 The solid and liquid phase thermal conductivities of the phase change material are λ s =0.2W / (m·K) and λ s =0.12W / (m·K), the true values ​​of the specific heat capacities of the solid and liquid phases of the phase change material are set to c s =2290 J / (kg·K) and c l =2110J / (kg·K), the incident heat flux on the surface is Figure 4 shown.

[0103] The method of the present invention is used to simultaneously measure the specific heat capacity and surface heat flux density of the solid-liquid phase change material, and the specific heat capacity of the solid phase and the liquid phase are obtained, respectively. s =2291.03 J / (kg·K) and c l =2109.50J / (kg·K), the surface heat flux density distribution is as follows Figure 5 shown.

[0104] The measurement errors of the specific heat capacity of solid and liquid materials are 0.0450% and 0.0711% respectively, and the measurement errors of surface heat flux density are as follows: Figure 6 As shown, the maximum error is less than 2.5%.

[0105] The present invention further provides a storage medium, which can be read by a computer or a processor and stores a computer program for executing the above method.

[0106] Those skilled in the art will appreciate that the above-mentioned embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. 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, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0107] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials, characterized in that: include: Step S1: Randomly initialize the position of each particle and give an initial guess of the surface heat flux density of the solid-liquid phase change material. Establish a solid-liquid phase change material internal coupling heat transfer model and set the current iteration number to k = 0; Step S2: Use laser to heat the surface of the solid-liquid phase change material, select M sampling points on the surface of the solid-liquid phase change material, and use an infrared thermal imager to measure the temperature of the M sampling points at N measurement times. Step S3: Based on the specific heat capacity c of the solid-liquid phase change material k and surface heat flux Solve the transient heat transfer model and numerically calculate the temperature of M measuring points at N measuring times Step S4: Based on the temperature measurement values ​​of M measuring points and calculated values Establish the input signal e for simultaneous measurement of specific heat capacity and surface heat flux density of solid-liquid phase change materials m,n and the particle individual fitness function F l ; Step S5: Construct a hybrid optimization module for simultaneous measurement of specific heat capacity and surface heat flux density of solid-liquid phase change materials. m,n and numerically calculated temperature Perform numerical optimization; Step S6: updating the specific heat capacity and surface heat flux density of the solid-liquid phase change material according to the optimization result; Step S7: Check whether the iteration stop condition has been met. If the stop condition is met, proceed to step S8 and return to step S3 to continue iterative update; Step S8: Record the specific heat capacity and surface heat flux density of the new solid-liquid phase change material at this time, output them as the measurement result, and end the measurement.

2. The method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials according to claim 1, characterized in that: The random initialization of each individual particle position in step S1 refers to randomly generating the position of each individual particle in the solution space, and using each individual particle position to represent a possible value of specific heat capacity. The initialization position is generated according to the following formula: Where R is a random number uniformly distributed in the interval [0,1], l is the lth particle individual, NL is the number of individuals in the particle group, the superscript 0 indicates the 0th iteration, i.e. initialization, and X max is the maximum value of the specific heat capacity of the solid-liquid phase change material, X min It is the minimum value of the specific heat capacity of solid-liquid phase change material.

3. The method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials according to claim 2, characterized in that: In step S1, the initial guess value of the surface heat flux density is given by the starting value of the measurement according to the external heat source characteristics of the solid-liquid phase transition material. The initial value of the surface heat flux density is set to C is a fixed positive number, NI is the number of reconstruction positions, and NJ is the number of reconstruction moments.

4. The method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials according to claim 1, characterized in that: In step S1, the internal heat transfer model of the solid-liquid phase change material includes two heat transfer modes: internal heat conduction and radiation of the solid-liquid phase change material; the heat transfer process is described by the following energy equation: Where ρ, c and λ represent density, specific heat capacity and thermal conductivity respectively, T and t represent temperature and time respectively. and f l denote the latent heat of phase change and the liquid fraction, respectively. Represents the divergence of the heat flux density of radiation heat transfer, which is obtained according to the following formula: Where Ω represents the direction of light transmission, r represents the spatial position, κ represents the absorption coefficient, and I represents the radiation intensity, which is obtained by solving the following radiation transfer equation: Among them, Ω′ represents the direction of external incident light, β and σ s represent the attenuation coefficient and scattering coefficient respectively, and Φ represents the scattering phase function.

5. The method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials according to any one of claims 1 to 4, characterized in that: The step S2 of selecting M sampling points on the surface of the solid-liquid phase change material is to select M temperature measurement points on the surface of the solid-liquid phase change material that are consistent with the simultaneous measurement positions of the surface heat flux density according to the measurement requirements of the surface heat flux density.

6. The method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials according to any one of claims 1 to 4, characterized in that: The numerical calculation in step S3 is the temperature of M measuring points at N measuring times It refers to the calculation obtained by solving the energy equation and the radiation transfer equation. The present invention uses the finite volume method to solve the energy equation and the radiation transfer equation to obtain it.

7. The method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials according to any one of claims 1 to 4, characterized in that: In step S4, the input signal e m,n and the particle individual fitness function F l , established as follows:

8. The method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials according to any one of claims 1 to 4, characterized in that: The hybrid optimization module in step S5 includes a particle swarm optimization module and a fuzzy reasoning module; the particle swarm optimization module performs group position optimization through NL particle individuals, and uses the position of each particle individual to represent a potential specific heat capacity measurement value; the moving speed and position of the particle individual are updated according to the following formula in each iteration: Among them, the superscript k1 is the number of inner loop iterations of the particle swarm optimization module, ω is the speed iteration weight factor, V is the individual particle moving speed, c1 and c2 are acceleration coefficients, r1 and r2 are random numbers uniformly distributed in the interval [0,1], P l is the position that the lth particle has searched so far to minimize the objective function, P g The position that minimizes the objective function found by the entire particle group so far.

9. The method for simultaneously measuring specific heat capacity and surface heat flux density of solid-liquid phase change materials according to any one of claims 1 to 4, characterized in that: The specific heat capacity c of the solid-liquid phase change material is updated in step S6 k and surface heat flux It is updated according to the following formula: The iteration stop condition refers to the following two conditions being met at the same time: Among them, ε1 and ε2 are two specified small positive numbers.

10. A storage medium, which can be read by a computer or a processor, characterized in that: The storage medium stores a computer program for executing any one of the methods in claims 1 to 9.

Images