TWI708157B - Data processing device, data processing method, and manufacturing method of solar cell module - Google Patents

Abstract

The data processing device (100) processes the measurement data obtained in the test for evaluating the durability of the solar cell module. The data processing device (100) includes: a related holding unit (21) that holds two parameters included in a plurality of parameters indicating the output characteristics of the solar cell module for items that cause deterioration of the solar cell module Correlation; and the estimation processing unit (16) compares the measurement data of the two parameters and the correlation to estimate the cause of deterioration.

Description

Data processing device, data processing method, and manufacturing method of solar cell module

The present invention relates to a data processing device, a data processing method, and a solar battery module for processing data obtained in a test for evaluating the durability of a solar battery module.

The reliability of solar cell modules is confirmed through endurance tests to evaluate durability in various environmental conditions. In the durability test, the output characteristics of the solar cell module are measured and the appearance of the solar cell module is visually inspected. In the measurement of output characteristics, the solar cell module is irradiated by suspected sunlight to generate power to obtain the measured values of various parameters, and then the preset reference values and measured values are compared to evaluate the output characteristics. The details of the durability test used to evaluate the durability of the solar cell module are regulated in various industrial standards.

Technicians engaged in the production of solar cell modules must confirm whether they have selected materials and set manufacturing conditions in order to ensure the durability of the product, and sometimes perform durability tests according to industrial specifications. In addition, in order to obtain useful information in a short period of time to review the materials of solar cell modules and the manufacturing conditions of solar cell modules, technicians sometimes conduct accelerated tests, that is, add deliberately to the durability test specified in industrial specifications. Conditions for accelerated degradation. When the technician confirms that there is deterioration that affects the durability of the product during its use, the technician examines the cause of the deterioration. By eliminating the causes specified by the inspection, it is possible to produce solar cell modules with durability that the product should satisfy.

In the past, in the inspection of the cause of deterioration, sometimes the image obtained by capturing the solar cell module in the excited light state under the applied voltage was analyzed, that is, the so-called EL (Electro-Luminescence) inspection was performed. Patent Document 1 discloses a technique for inspecting defects in inspection objects based on data processing performed on images taken by making solar cell modules emit light. Advanced technical literature

Patent Document 1: International Publication No. 2011/016420

In the case of the conventional EL inspection disclosed in Patent Document 1, when the deterioration has not progressed to the degree of deterioration used as a criterion for pass judgment in the endurance test, it may be difficult to detect the cause of the deterioration. Therefore, it is sometimes necessary to wait for the deterioration to proceed before obtaining information to verify the cause of the deterioration. In addition, regarding most of the degradations that may occur in the solar cell module, it is difficult to identify the cause of the measured value of each parameter obtained from the measurement of the output characteristics in the conventional endurance test. Therefore, the conventional technology has a problem that it is difficult to detect the cause of deterioration that occurs in the solar cell module in a test for evaluating the durability of the solar cell module.

In view of the above-mentioned problems, the purpose of the present invention is to obtain a data processing device that can easily detect the cause of the deterioration of the solar cell module in a test for evaluating the durability of the solar cell module.

In order to solve the above-mentioned problems and achieve the objective, the data processing device of the present invention processes the measurement data obtained in the test for evaluating the durability of the solar cell module. The data processing device of the present invention includes: a correlation holding unit that holds the correlation between two parameters included in a plurality of parameters indicating the output characteristics of the solar cell module for matters that cause degradation of the solar cell module; And the estimation processing unit compares the measurement data and correlation between the two parameters to estimate the cause of deterioration.

The data processing device of the present invention achieves the effect of easily detecting the cause of the deterioration occurring in the solar cell module in a test for evaluating the durability of the solar cell module.

Hereinafter, the data processing device, the data processing method and the manufacturing method of the solar cell module of the embodiment of the present invention will be described in detail based on the drawings. In addition, the present invention is not limited to this embodiment. [Implementation Type 1]

FIG. 1 is a block diagram showing the structure of an evaluation system 110 having a data processing device 100 according to Embodiment 1 of the present invention. The evaluation system 110 is a system for evaluating the durability of the produced solar cell module. The evaluation system 110 includes an output measuring device 101, an EL inspection device 102, and a data processing device 100. The output measuring device 101 measures the output characteristics of the solar cell module. The EL inspection device 102 performs EL inspection of the solar cell module. The data processing device 100 processes the data input from the output measuring device 101 and the data input from the EL inspection device 102. In the following description, the manufacture of solar cell modules includes the manufacture of solar cell modules and the durability evaluation of the manufactured solar cell modules.

The evaluation system 110 evaluates the durability of the solar cell module based on the test result of the durability test or the accelerated test. The endurance test is a test used to evaluate the durability of solar cell modules under various environmental conditions, and is regulated by various industrial standards. The durability test is based on, for example, the test specifications IEC61215 and IEC61701 for solar cell modules set by the International Electrotechnical Commission (IEC). The accelerated test is a test in which conditions for deliberately accelerated deterioration are added to the endurance test specified in the industrial specifications. In the following description, the durability test and the accelerated test are not distinguished, and are simply referred to as "tests".

In the test, the solar cell module is periodically irradiated with suspected sunlight to generate electricity. The output measuring device 101 measures the current and voltage output by the solar cell module. The EL inspection device 102 takes an image of the solar cell module in the excitation light state by applying a voltage every predetermined period.

The data processing device 100 is a computer installed with a program (that is, a data processing program) for implementing the data processing method of the implementation pattern 1. The data processing device 100 processes the data obtained in the test of the manufactured solar cell module. The functional parts of the data processing device 100 shown in FIG. 1 are implemented by a computer (hardware) executing a data processing program.

The data processing device 100 includes a control unit 10, and the control unit 10 is a functional unit that controls the entire data processing device 100. The control unit 10 includes a calculation unit 14, a data processing unit 15, an estimation processing unit 16, and a connection setting unit 17. The calculation unit 14 is a functional unit that performs calculation processing on the measurement result of the output measuring device 101 and performs a pass judgment of durability. The data processing unit 15 is a functional unit that processes the measurement data obtained in the test. The estimation processing unit 16 is a functional unit for determining the cause of deterioration of the solar cell module that has been deteriorated in the estimation test. The relational connection setting unit 17 is a functional unit that sets relational connections of parameters. The description of the parameters will be described later.

The data processing device 100 includes a storage unit 11, which is a functional unit for storing information. The storage unit 11 has a measurement data storage unit 18 and an image data storage unit 19. The measurement data storage unit 18 is a functional unit that stores measurement data obtained in the test. The image data storage unit 19 is a functional unit that stores image data obtained by the EL inspection in the test. The measurement data storage unit 18 stores the measurement data respectively obtained by using plural parameters in the test. The storage unit 11 has a processing data storage unit 20, a related holding unit 21, and a setting holding unit 22. The processing data storage unit 20 is a functional unit that stores processing data obtained after data processing by the data processing unit 15. The correlation holding unit 21 is a functional unit that holds information indicating the correlation between the two parameters included in the plural parameters of the output characteristics of the solar cell module for each item that is the cause of deterioration of the solar cell module. The setting holding unit 22 is a functional unit that holds the setting of the association connection. The estimation processing unit 16 estimates the cause of the deterioration by comparing the measurement data of the two parameters and the correlation relationship.

The data processing device 100 includes a receiving unit 12 and a presentation unit 13. The receiving unit 12 is a functional unit that receives and outputs the measured value measured by the measuring device 101 and the image obtained by the EL inspection device 102. The presentation unit 13 presents information about durability evaluation and the result estimated by the estimation processing unit 16.

FIG. 2 is a block diagram showing the hardware structure of the data processing device 100 of the first embodiment. The data processing device 100 includes a CPU (Central Processing Unit) 41 that executes various processes, a RAM (Random Access Memory) 42 including a data storage area, a ROM (Read Only Memory) 43 that is a non-volatile memory, and an external memory device 44. The data processing device 100 includes a communication interface (Interface, I/F) 45, an input device 46, and a display 47. The communication interface 45 is a connection interface between the data processing device 100 and external devices. The input device 46 inputs information according to the operation of the technician. The display 47 is an output device that displays information on a screen. The various parts of the data processing device 100 shown in FIG. 2 are connected to each other through a bus 48.

The CPU 41 executes programs stored in the ROM 43 and the external memory device 44. The functions of the control unit 10 shown in FIG. 1 are realized by the CPU 41. The external memory device 44 is a HDD (Hard Disk Drive) or an SSD (Solid State Drive). The external memory device 44 stores data processing programs and various data. The function of the storage unit 11 shown in FIG. 1 is realized by the external storage device 44. The ROM 43 stores a basic control program BIOS (Basic Input/Output System) or UEFI (Unified Extensible Firmware Interface) that becomes the basis of the data processing device 100 (that is, a computer). In addition, the data processing program can also be stored in ROM43.

The programs stored in the ROM 43 and the external memory device 44 are loaded into the RAM 42. The CPU 41 expands the data processing program in the RAM 42 and performs various processing. The input device 46 includes a keyboard and a pointing device. The function of the notification unit 13 shown in FIG. 1 is realized using the display 47. The function of the receiving unit 12 shown in Fig. 1 is realized by the communication I/F 45.

The data processing program may also be a program stored in a computer-readable memory medium. The data processing device 100 may also store the data processing program stored in the storage medium to the external storage device 44. The storage medium can also be a portable storage medium such as a flexible disc, or a flash memory such as a semiconductor memory. The data processing program can also be installed to the computer that becomes the data processing device 100 from another computer or a server device through a communication network.

The function of the data processing device 100 can be realized by a dedicated hardware (processing circuit) for evaluating the durability of the solar cell module. The processing circuit is a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), or a combination of them.

Next, a description will be given of the solar cell module to be evaluated by the system 110 to be evaluated. Fig. 3 is a cross-sectional view of the main part of the solar cell module 50 whose durability is evaluated by the evaluation system 110 shown in Fig. 1. Fig. 4 is a plan view showing the structure on the light-receiving surface side of the solar battery cell 51 included in the solar battery module 50 shown in Fig. 3. Fig. 5 is a plan view showing the structure of the back side opposite to the light-receiving surface side of the solar battery cells 51 included in the solar battery module 50 shown in Fig. 3.

The solar battery module 50 has a plurality of solar battery cells 51. The plurality of solar battery units 51 are electrically connected by the connecting wires 52. The plural solar battery cells 51 are connected in series in the X direction shown in FIGS. 3 to 5. The solar cell 51 has a semiconductor substrate 53, an anti-reflection film, a light-receiving surface electrode 54, and a back surface electrode 55. The semiconductor substrate 53 is a solar cell substrate having a photoelectric conversion function, and has a pn junction. The anti-reflection film and the light-receiving surface electrode 54 are formed on the light-receiving surface of the semiconductor substrate 53. The back surface electrode 55 is formed on the back surface of the semiconductor substrate 53.

The light-receiving surface of the semiconductor substrate 53 is formed with an uneven texture structure useful for improving light collection efficiency. The texture structure is a collection of tiny structures in a quadrangular pyramid shape. The light-receiving surface electrode 54 is provided surrounded by an anti-reflection film. In Figs. 3 and 4, the illustration of the texture structure and the anti-reflection film is omitted.

The light-receiving surface electrode 54 has a collecting electrode 54A and a connection electrode 54B. The collector electrode 54A is a linear gate electrode that collects electrons generated due to photoelectric conversion on the semiconductor substrate 53. The connection electrode 54B is arranged orthogonal to the collecting electrode 54A, and is a bus electrode that takes out electrons from the collecting electrode 54A. The back electrode 55 has a collector electrode 55A and a connection electrode 55B. The collector electrode 55A collects the holes generated by the photoelectric conversion on the semiconductor substrate 53. The connecting electrode 55B takes out holes from the collecting electrode 55A. The collector electrode 55A is provided on the entire back surface of the solar battery cell 51. The collector electrode 55A contains aluminum. The connection electrodes 55B are scattered inside the solar cell 51. The connection electrode 55B is provided at a position facing the connection electrode 54B with the semiconductor substrate 53 interposed therebetween. The connection electrode 55B contains silver. The connecting electrode 54B of one solar battery cell 51 and the connecting electrode 55B of the other solar battery cell 51 among the solar battery cells 51 adjacent to each other in the X direction are connected through the connecting wire 52.

The plural solar battery cells 51 are sealed by the transparent resin 56 of the sealing material. The cover glass 57 as a protective part covers the light-receiving surface side of the plural solar battery cells 51 sealed by the transparent resin 56. The back sheet 58 as a protective part covers the back side of the plurality of solar battery cells 51 sealed by the transparent resin 56.

Next, the measurement of the output characteristics of the solar cell module 50 will be described. The evaluation system 110 evaluates the output characteristics of the solar battery module 50 by analyzing various parameters showing the characteristics after replacing the solar battery module 50 with an equivalent circuit. The data processing device 100 determines whether the solar cell module 50 has the durability that the product should satisfy based on changes in the elapsed time of the measured values of various parameters obtained in the test. The calculation unit 14 uses the measurement results of current and voltage to calculate measurement values of various parameters used to evaluate the durability of the solar cell module 50.

Figure 6 shows the equivalent circuit of the solar cell module shown in Figure 3. The solar cell module 50 is replaced with an equivalent circuit having a current source 61, a parallel impedance 62, a series impedance 63, and a diode 64. The current source 61 is a power source from which photocurrent flows. The parallel impedance 62 represents the impedance generated by leakage current and the like around the pn junction. The series impedance 63 represents the impedance when current flows through each part of the element. The output characteristic of the solar cell module 50 is represented by the characteristics of the current I and the voltage V of the diode 64 included in the equivalent circuit. In the following description, the characteristics of current I and voltage V may be referred to as IV characteristics. The calculation unit 14 obtains the output characteristics (IV characteristics) of the solar cell module 50 based on the measurement results of the current I and the voltage V.

Fig. 7 is an example of a graph showing the IV characteristic of the solar cell module 50 shown in Fig. 3. In the graph shown in Fig. 7, the vertical axis represents current I and the horizontal axis represents voltage V. When the bias voltage of the load connected to the output terminal of the solar cell module 50 changes, the data processing device 100 measures the current I and the voltage V output from the output terminal of the solar cell module 50 to obtain the representative current I The graph (curve) of the relationship with the voltage V. This curve represents the IV characteristic of the solar cell module 50. In FIG. 7, a curve showing the IV characteristic when the solar cell module 50 is irradiated with light, and a curve showing the IV characteristic when the solar cell module 50 is not irradiated with light is shown.

The calculation unit 14 calculates the measured values of the parameters of the maximum output power Pmax, the open circuit voltage Voc, and the short circuit current Isc based on the IV characteristics when the light is irradiated. Pmax represents the maximum value of the product of the electric power I and the voltage V (that is, electric power) on the curve. Voc is the voltage V when I=0. Voc represents the voltage V when the output terminal of the solar cell module 50 is not connected to a load. Isc is the current I when V=0. Isc represents the current I when the output terminal of the solar cell module 50 is short-circuited. Pmax is the product Ipm×Vpm of the current I=Ipm at the maximum output power and the voltage V=Vpm at the maximum output power.

The calculation unit 14 calculates the measured values of the short-circuit current density Jsc, the conversion efficiency Eff, the curve factor FF (Fill Factor), the series impedance Rs, the parallel impedance Rsh, and the current value Id. Jsc is the result of dividing Isc by the area of the light-receiving surface of the solar cell 51. Eff is the result of dividing Pmax by the intensity of the light irradiating the solar battery cell 51. FF is the result of dividing Pmax by the product of Voc and Isc. The closer the FF value is to 1, the higher the conversion efficiency of the solar cell module 50 is.

The series impedance Rs is represented by the slope at Voc, that is, around I=0 among the curves representing the IV characteristics when irradiated with light. The parallel impedance Rsh is represented by the slope of I=Isc in the curve representing the IV characteristic when light is irradiated. The current value Id is the value of the current I flowing in the direction opposite to the forward direction when a predetermined negative bias voltage is applied to the solar battery module 50 when the solar battery module 50 is not irradiated with light.

The calculation unit 14 calculates the measured values of Pmax, Voc, Isc or Jsc, Eff, FF, Rs, Rsh, and Id through calculation processing. The measurement data storage unit 18 stores the calculated measurement value. In addition, the parameters of the measurement value calculated by the calculation unit 14 are not limited to the parameters described in the first embodiment. The calculation unit 14 may also calculate the measured values of parameters other than the parameters described in the first embodiment.

In the experiment, the solar cell module 50 was generated to generate electricity every predetermined period, and the output measuring device 101 was used for measurement. The output measuring device 101 transmits the measured values of the current and voltage output by the solar cell module 50 to the data processing device 100. The calculation unit 14 calculates the measurement values of various parameters in each period based on the measurement values received by the receiving unit 12. The calculation unit 14 detects changes in the elapsed time of the measured value of each parameter. When a decrease in the measured value from the beginning of the test is confirmed with the passage of time, it is estimated that the solar cell module 50 has deteriorated to reduce the output characteristics. The calculation unit 14 determines the presence or absence of deterioration of the solar cell module 50 based on the time change of the measured value of each parameter. The measurement data storage unit 18 stores measurement results (measurement data) of various parameters.

Next, the EL inspection performed by the EL inspection device 102 will be described. Fig. 8 schematically shows the EL image 65 obtained by the EL inspection device 102 included in the evaluation system 110 shown in Fig. 1. The EL inspection device 102 photographs the solar cell module 50 in the excitation light state due to the application of voltage. The calculation unit 14 analyzes an image (EL image 65) obtained by shooting of the solar cell module 50. FIG. 8 shows the EL image 65 of one solar cell unit 51 in the solar cell module 50.

When the solar cell module 50 is in an excited light state, the semiconductor substrate 53 in the solar cell unit 51 emits light. The EL image 65 shows the image of the light-receiving surface electrode 54 and the back electrode 55 of the solar cell 51. Since the collecting electrode 54A has a width smaller than the resolution of the EL image 65, the image of the collecting electrode 54A is not confirmed in the EL image 65. The EL image 65 shows the image of the connecting electrode 54B and the connecting electrode 55B. In the EL image 65, in areas other than the image of the light-receiving surface electrode 54 and the back electrode 55, the part where the current passes will light up and become brighter, and the part where no current passes will become dark. When a defect such as a crack of the semiconductor substrate 53 occurred, no current would flow in the portion where the defect occurred. Therefore, it was confirmed that a dark portion was formed in the EL image 65. The calculation unit 14 detects the defects of the solar cell module 50 through the analysis of the EL image 65. The calculation unit 14 may define a portion of the EL image 65 whose brightness is below the threshold value as a dark portion, and observe the dark portion.

In the EL inspection of the test, the EL inspection device 102 photographs the solar cell module 50 every predetermined period. The EL inspection device 102 transmits the data (image data) of the EL image 65 obtained by shooting to the data processing device 100. The calculation unit 14 analyzes the image data received by the receiving unit 12. The calculation unit 14 observes the change of the elapsed time of the EL image 65 by analyzing the image data. In the case where the bright part of the EL image 65 at the beginning of the test becomes darker with the passage of time, it is presumed that this part has been degraded to degrade the performance of photoelectric conversion. The calculation unit 14 determines the presence or absence of deterioration of the solar cell module 50 based on changes in the elapsed time of the EL image 65. The image data storage unit 19 stores image data.

In this way, the data processing device 100 determines whether the solar cell module 50 has deteriorated based on the changes over time in the measured values of each parameter and the changes over time in the dark part in the EL image 65. The evaluation system 110 evaluates the durability of the solar cell module 50 based on the determination of the presence or absence of deterioration. The presentation unit 13 presents the durability evaluation result.

Fig. 9 is a flowchart showing the first operation procedure of the evaluation system 110 shown in Fig. 1. The first operation step is a step for presenting the results of the durability evaluation performed by the test.

In step S1, the evaluation system 110 performs the measurement of the output characteristics and the EL inspection at the start of the test on the produced solar cell module 50. The calculation unit 14 calculates the measured values of various parameters based on the current and voltage measurement results made by the output measuring device 101. The measurement data storage unit 18 stores the calculated measurement value (measurement data). The EL inspection device 102 photographs the solar cell module 50 in the excitation light state. The image data storage unit 19 stores data (image data) of the EL image 65 obtained during shooting.

When the measurement of the output characteristics and the EL inspection in step S1 are completed, the durability test or the accelerated test of the solar cell module 50 is started. In step S2, the evaluation system 110 performs output characteristic measurement and EL inspection every set time within the test time. The measurement data storage unit 18 stores the calculated measurement value (measurement data). The data processing unit 15 will create time series data of each parameter based on the measurement data stored in the measurement data storage unit 18. The processing data storage unit 20 stores the time series data created by the data processing unit 15. In addition, the data processing unit 15 creates a graph showing the transition of the measurement data for each parameter. The image data storage unit 19 stores image data obtained by shooting.

The calculation unit 14 obtains the ratio of the change over time of the measurement data of each parameter based on the time series data stored in the processing data storage unit 20. Based on the image data stored in the image data storage unit 19, the calculation unit 14 confirms whether there is a dark area in the EL image 65 that changes with time. In step S3, the calculation unit 14 will determine whether the solar cell module 50 has deteriorated based on the change over time of the measurement data of each parameter and the change over time of the dark part in the EL image 65. The calculation unit 14 determines whether the durability evaluation (test) is acceptable. In step S4, the presentation unit 13 presents the durability evaluation result in step S3. Thereby, the evaluation system 110 ends the first operation step shown in FIG. 9.

In the humidity resistance test, which is one of the durability tests, the durability of the solar cell module 50 when used and stored in a high temperature and high humidity state is evaluated. This humidity resistance test is also called the Damp Heat (DH) test. For example, in the humidity resistance test, the test conditions are set to a temperature of 85°C and a relative humidity of 85%, and the test time is set to 1000 hours. In the humidity resistance test, the output characteristics are measured every 500 hours.

In Embodiment 1, instead of the humidity resistance test specified in the specifications, an accelerated test related to humidity resistance is implemented. The test conditions of the accelerated test will be more stringent than the endurance test. For example, in an accelerated test related to humidity resistance, the test conditions are set to a temperature of 105°C and relative humidity to 100%, and the test time is set to be shorter than 1000 hours. The evaluation system 110 measures the output characteristics every 115 hours. In the accelerated test related to humidity resistance, the size of the test tank that can satisfy the test conditions can be considered, and the part of the solar cell module 50 equivalent to one solar cell 51 is regarded as the sample. The accelerated test of moisture resistance is carried out by putting a plurality of specimens into a test tank.

Next, the estimation of the cause of deterioration performed by the data processing device 100 will be described. The data processing device 100 performs data processing for estimating the cause of the deterioration for the solar cell module 50 determined to be deteriorated, and presents the estimation result. The technician will specify the cause of the deterioration according to the content of the suggested result. The re-evaluation of materials or manufacturing conditions that are the cause of deterioration will be carried out by technicians, and by eliminating the cause of deterioration, it is possible to ensure that the solar cell module 50 to be produced in the future has the durability that the product should satisfy.

The relational connection setting unit 17 sets the relational connection of two parameters, and these parameters are included in the plural parameters used to evaluate the durability of the solar cell module 50. The setting holding unit 22 holds the content of the related link set by the related link setting unit 17. The data processing unit 15 combines the measurement data of the two parameters in accordance with the settings held by the setting holding unit 22, thereby performing data processing and associating the measurement data of the two parameters. The processing data storage unit 20 stores a combination of measurement data obtained after data processing.

The correlation holding unit 21 holds a function (correlation function) showing a correlation relationship grasped in advance for each deterioration cause for the two parameters for which the correlation is set. In the correlation holding unit 21, information indicating the cause of deterioration is correspondingly linked to the correlation function and held. The estimation processing unit 16 compares the distribution of the measurement data of the two related parameters with the correlation function held by the correlation holding unit 21 in accordance with the settings held by the setting holding unit 22 to estimate the cause of the deterioration.

The data processing device 100 presents a correlation diagram in which the two parameters included in the plural parameters are related and connected, so as to provide for the reasons that are difficult to estimate from the IV characteristics and the time series data of each parameter, and provide the possibility of easier reduction. Information on the scope of the matter. The associative connection of the two parameters made by the associative connection setting unit 17 will be performed through manual input of the input device 46 by a technician. The technician can set to the data processing device 100 an association link that is useful for narrowing down the scope of the possible cause more easily. The data processing device 100 can set the related link of arbitrary content due to the related link setting unit 17. The number of association links that can be set is assumed to be arbitrary.

Fig. 10 is a flowchart showing the second operation procedure of the evaluation system 110 shown in Fig. 1. The second operation step is a step for presenting the estimation result of the cause of deterioration. In step S11, the relational connection setting unit 17 sets the relational connection of two parameters included in a plurality of parameters representing the output characteristics of the solar cell module 50. The setting holding unit 22 holds the content of the related link set by the related link setting unit 17. The data processing device 100 performs related link setting and related link content retention before the start of the test. The correlation function described above is held in the correlation holding unit 21 in advance. The correlation function may also be set in the data processing device 100 by a technician, or may be set in a data processing program in advance. A technician can set an arbitrary correlation function to the data processing device 100 even if the correlation function is preset to the data processing program.

When the measurement of the output characteristics in the above steps S1 and S2 is performed, the measurement data storage unit 18 will store the measurement data obtained for each plural parameter. In step S12, the data processing unit 15 processes the measurement data of the two parameters in a relational connection according to the retained settings, thereby generating a combination of measurement data. The processing data storage unit 20 stores a combination of measurement data obtained by data processing. The combination of measurement data will be represented by the coordinates of the correlation diagram. The correlation diagram is a scatter diagram with two axes used to represent parameters that are related to each other. The presentation unit 13 presents the correlation diagram created by the data processing unit 15.

After the creation and storage of the combination of measurement data during the test time is completed, in step S13, the estimation processing unit 16 compares the relationship between the measurement data of the two related parameters and the correlation function held in the correlation holding unit 21, thereby Determine whether there are similar correlation functions in the relationship of the measurement data. The estimation processing unit 16 calculates an index indicating the degree of similarity between the distribution of the measurement data in the correlation graph and the correlation function, and determines whether there is a similarity based on the calculated index. The estimation processing unit 16 can use any method to determine whether they are similar.

When there is a correlation function with a relationship similar to the measurement data (step S13: Yes), in step S14, the estimation processing unit 16 extracts from the correlation holding unit 21 cause information that has a corresponding link with the correlation function , In order to infer the cause of deterioration. The estimation processing unit 16 outputs the estimation result obtained in step S14. In this manner, the estimation processing unit 16 obtains from the correlation holding unit 21 cause information that has a corresponding connection with the correlation function that is similar to the measurement data, and executes processing for estimating the cause of deterioration. In step S15, the presentation unit 13 presents the estimation result output by the estimation processing unit 16.

When there is no correlation function similar to the relationship of the measurement data (step S13, No), the estimation processing unit 16 outputs an estimation result of "the reason to be estimated is no." In step S15, the presentation unit 13 presents the estimation result that "the reason to be estimated is none". With this, the evaluation system 110 ends the steps shown in FIG. 10.

The technician will refer to the estimation result presented by the presentation unit 13 to perform an inspection to verify the cause of deterioration. For example, a technician will perform a damage inspection to observe the inside of the solar cell module 50 by cutting off the solar cell module 50 or a method equivalent to that of cutting off. When the presentation unit 13 presents the cause information, the technician will narrow down the scope of the presented cause information and perform an inspection, thereby making it possible to easily verify the cause of the deterioration. When the presentation unit 13 does not present the cause information, the technician can narrow down the scope of the object and perform inspections other than the cause of the information held by the relevant holding unit 21.

The technician can also set the new correlation connection of the two parameters and the new correlation function of the two parameters based on the correlation between the two parameters newly found due to the verification of the deterioration reason. By repeating such investigations, the data processing device 100 accumulates useful information for estimating and specifying the cause of deterioration. The data processing device 100 can perform high-precision estimation of the cause of deterioration due to the accumulation of useful information.

Next, specific examples of the correlation between the two parameters and the estimation of the cause of deterioration will be described. FIG. 11 illustrates the first example of the association between two parameters set by the data processing device 100 shown in FIG. 1. The first example is an example in which the curve factor FF and the series impedance Rs are linked and connected. The setting holding unit 22 holds the setting regarding the correlation between the first parameter FF and the second parameter Rs. Figure 11 shows the correlation diagram in the state before the measurement data of FF and Rs are drawn. In the graph shown in Fig. 11, the vertical axis represents Rs and the horizontal axis represents FF.

In the data processing device 100, three correlation functions for FF and Rs are set, and these three correlation functions show the correlation that can be grasped for each deterioration cause. The correlation holding unit 21 holds three correlation functions and cause information corresponding to each correlation function. In the correlation diagram shown in FIG. 11, graphs C1, C2, and C3 of three correlation functions held by the correlation holding unit 21 are added. In the correlation diagram of FF and Rs, the graphs C1, C2, and C3 will be represented by straight lines. Hereinafter, the correlation function represented by the graph C1 is taken as the first correlation function, the correlation function represented by the graph C2 is taken as the second correlation function, and the correlation function represented by the graph C3 is taken as the third correlation function.

The first correlation function is a function that expresses the correlation formed by the variation of series impedance such as an individual increase in series impedance and a monotonous decrease. The deterioration tendency indicated by the first correlation function appears due to the deterioration of the humidity resistance of the entire solar battery cell 51 in the plane direction shown in FIGS. 3 to 5. The surface direction refers to a direction parallel to the light-receiving surface and the back surface of the solar cell 51. In the manufacturing process of the solar battery cell 51, when the cross-sectional area of the connection wiring 52 is made smaller than the original one to increase the series impedance of the solar battery module 50, this correlation is confirmed between FF and Rs. According to this correlation, when the structure of the solar cell module 50 is coupled with a series impedance of 0.001Ω, the value of FF will be reduced by 0.01. The correlation holding unit 21 associates and holds information on the cause of the increase in the serial impedance caused by the deterioration of the moisture resistance of the entire solar battery cell 51 with the first correlation function.

The first correlation function represented by the graph C1 corresponds to the correlation in the case where a monotonous increase in the series impedance of the solar battery cell 51 occurs. This correlation may occur when the connecting electrode 55B inside deteriorates, for example. Specifically, it appears when the contact resistance between the connection electrode 55B and the collector electrode 55A inside increases. Or, it appears when the contact resistance between the connection electrode 55B and the connection wiring 52 inside increases. Because the impedance of the connection wiring 52 itself is low, when the contact between the collector electrode 55A, the connection electrode 55B, and the connection wiring 52 is abnormal, the same correlation as when the series impedance increases monotonously occurs.

The second correlation function is a function representing the correlation between the impedance of the light-receiving surface electrode 54 and the impedance of the back electrode 55 in the surface direction. The deterioration tendency represented by the second correlation appears due to the deterioration of the moisture resistance of the solar battery cell 51 in the surface direction. When an impedance distribution occurs in a region with a size of 1 mm or more, the correlation is confirmed between FF and Rs. In this case, the IV characteristic of the solar cell module 50 will be the same as the IV characteristic of the circuit in which the solar cell units 51 having different series impedances Rs are connected in parallel. In the second correlation function, compared with the case of the first correlation function, the decrease in FF is larger than the increase in Rs.

When the water around the solar cell module 50 enters the inside of the solar cell module 50 from one end of the solar cell module 50, the solar cell 51 located at the end of the solar cell module 50 will flow from the solar cell 51 Water enters at one end. The deterioration of the solar battery unit 51 caused by water ingress usually starts from one end of the solar battery unit 51. In the manufacturing process of the solar battery cell 51, when a part of the collector electrode 54A shown in Fig. 4 is intentionally disconnected, or when a part of the back electrode 55 is made thinner than the original thickness, the This correlation was confirmed between FF and Rs. The correlation holding unit 21 associates and holds the cause information of the impedance distribution caused by the deterioration of the moisture resistance of the solar battery cell 51 with the second correlation function.

The correlation of the second correlation function represented by the graph C2 appears when a part of the electrode is deteriorated, for example. Specifically, among the gate electrodes (collecting electrodes 54A) on the light-receiving surface side, only when the end of the solar cell 51 is deteriorated, or the connecting electrode 54B on the light-receiving surface and the current-collecting electrode on the light-receiving surface The contact resistance between a part of 54A increases. In other words, it appears in all the positions where the connecting electrode 54B on the light receiving surface and the collecting electrode 54A on the light receiving surface are in contact with one part being normal, and the other part is degraded when the contact resistance increases. When the contact resistance between a part of the connection electrode 54B on the light-receiving surface and the collecting electrode 54A on the light-receiving surface increases, a phenomenon occurs that current is collected in the normal contact portion (collector electrode 54A). Because Rs has a slope near I=0, even if the contact resistance increases at a part of the position, Rs will not change significantly when current flows through the normal contact part, but due to the increase of the contact resistance at some positions , Vpm and Ipm at maximum output power are reduced. Because of the decrease in Vpm and Ipm, if the maximum output power Pmax decreases, FF will decrease. Therefore, in the second correlation function, the decrease in FF relative to the increase in Rs is larger than in the case of the first correlation function, which represents the correlation when the series impedance simply increases.

The third correlation function represents the correlation between the increase in the contact resistance of the light-receiving surface electrode 54 and the decrease in the change in the contact resistance. This impedance may change in the contact impedance between the collector electrode 54A of the light-receiving surface electrode 54 and the semiconductor substrate 53 (emitter). The deterioration tendency indicated by the third correlation function generally occurs in the deterioration of the solar cell module 50, and appears when the contact resistance partially increases in the surface direction. In the case where the contact resistance of the collector electrode 54A is intended to be changed due to the change in the firing conditions of the electrode firing in the manufacturing step of the solar battery cell 51, the correlation between FF and Rs is confirmed.

The change in the contact resistance of the collector electrode 54A partially occurs on the light-receiving surface of the solar cell. In the area of the semiconductor substrate 53 that is in contact with the collector electrode 54A, there are many parts with a higher contact resistance than the surrounding area in the order of 1 μm or 10 μm.

The apex or ridge of the structure forming the texture structure formed on the semiconductor substrate 53 is in contact with the current collector electrode 54A, and an alloy layer formed by the reaction of silver included in the current collector electrode 54A and silicon included in the semiconductor substrate 53 is formed . The electrical connection between the collector electrode 54A and the semiconductor substrate 53 is ensured through the alloy layer. The length of the bottom side of the bottom surface and the height from the bottom surface to the apex of the structure are arbitrary in the order of 1 μm to the order of 10 μm. Therefore, the contact between the collector electrode 54A and the semiconductor substrate 53 will also occur every 1 μm or Field variation of the order of 10μm. Because of this contact variation, the contact resistance of the collector electrode 54A may vary. The correlation holding unit 21 associates and holds information on the cause of the increase in the contact resistance portion of the light-receiving surface electrode 54 in the surface direction with the third correlation function.

In the third correlation function, compared with the case of the first correlation function, the decrease in FF is larger than the increase in Rs. In the third correlation function, the decrease in FF relative to the increase in Rs is smaller than in the case of the second correlation function.

The correlation of the third correlation function represented by the graph C3 appears when, for example, the contact resistance between the collector electrode 54A of the light-receiving surface and the semiconductor substrate 53 increases. When the contact resistance between the collector electrode 54A of the light-receiving surface and the semiconductor substrate 53 increases, a phenomenon occurs that current is collected on the collector electrode 54A having a normal contact resistance. The portion where the collector electrode 54A contacts the semiconductor substrate 53 is present in a wide area on the entire light-receiving surface. Therefore, the third correlation function is compared with the case of the second correlation function which shows the correlation when a part of the electrode is deteriorated. The decrease in FF becomes smaller relative to the increase in Rs.

In addition, the correlation function is not limited to being represented by a linear graph, and may be represented by a curved graph.

Fig. 12 shows an example of time-series data in which a curve factor, which is one of the related parameters, is set by the data processing device 100 shown in Fig. 1. In the graph shown in Figure 12, the vertical axis represents the curve factor FF, and the horizontal axis represents time.

Based on the measurement data stored in the measurement data storage unit 18, the data processing unit 15 creates time series data about complex parameters including FF. The data processing unit 15 creates a graph showing the transition of time series data for each parameter. The data processing unit 15 creates a figure as shown in Fig. 12 for the FF. Figure 12 shows the time series data of 5 specimens. Time series data will be represented by trace points showing the measurement data every 115 hours.

In Figure 12, the time "0h" indicates the start of the test. After 115 hours from the start of the test, FF slowly decreased. After 920 hours from the start of the test, the FF in each sample dropped by about 2% to 3%.

Fig. 13 is a first diagram showing an example of the distribution of measurement data of the curve factor and series impedance due to the correlation and connection of the two parameters of the first example shown in Fig. 11. Figure 13 is the trace point of the additional measurement data on the correlation diagram shown in Figure 11. The data processing unit 15 generates coordinates representing the combination of the measured value of FF and the measured value of Rs, thereby creating a combination of measured data of FF and Rs. The data processing unit 15 draws the generated coordinates on the correlation diagram.

In this way, the data processing unit 15 generates a graph representing the measured value of FF and Rs on the graph representing the horizontal axis of FF and the vertical axis of Rs for the first parameter FF and the second parameter Rs that have been set to be linked. The correlation diagram of the coordinate of the combination of measured values. The presentation unit 13 presents the correlation diagram generated by the data processing unit 15. In this way, the data processing device 100 can present the relationship between the measurement data of FF and Rs that are associated with each other in a visually easy-to-understand type.

The correlation diagram shown in Figure 13 depicts the measured data of FF and Rs for 920 hours from the start of the test. The data processing unit 15 creates a correlation diagram as shown in FIG. 13 for FF and Rs. Figure 13 shows the measurement data of 5 specimens. The dots at the bottom right in the area where the dots are scattered indicate the measurement data at the beginning of the experiment. As time passes, FF decreases as Rs increases. In the area where the trace points are scattered, the trace point at the upper left end represents the measurement data after 920 hours.

The estimation processing unit 16 compares the slope of the straight line L1 obtained by the linear approximation of the drawing points and the slopes of the graphs C1, C2, and C3 of the respective correlation functions, thereby judging whether there is a correlation function similar to the measurement data. According to the correlation diagram shown in FIG. 13, the slope of the straight line L1 is closest to the slope of the graph C3 among the graphs C1, C2, and C3.

When the firing temperature of electrode firing in the manufacturing step of the solar battery cell 51 becomes higher, the contact resistance of the collector electrode 54A decreases, and Rs becomes lower. When the firing temperature becomes lower, the contact resistance becomes higher and Rs becomes higher. The inventors have confirmed that when the firing temperature is raised and lowered when the firing temperature is the highest, and the firing temperature is lowered more than usual, the moisture resistance of the solar battery cell 51 decreases, indicating the description of the measurement data of FF and Rs. The dots form the inclined distribution shown in Figure 13. Such a drop in moisture resistance can also be confirmed by the moisture resistance test specified in the specifications.

The estimation processing unit 16 determines that the relationship between the measurement data of FF and Rs is similar to the third correlation relationship, and obtains the cause information having the corresponding connection with the third correlation function from the correlation holding unit 21. In this case, the cause information is used in this way, and the estimation processing unit 16 compares the measurement data of FF and Rs with the stored correlation function to estimate the cause of the deterioration.

The presentation unit 13 displays the relationship between the measurement data of the two parameters set to be linked together on the correlation graph together with the graph of the correlation function. In this way, the data processing device 100 can easily comprehendly present the relationship between the measurement data of the two parameters related to each other.

The correlation holding unit 21 may also store the relationship between the measurement data of FF and Rs and the comparison result of the maintained correlation, and accumulate the tendency of the distribution of the measurement data and the specified reason at any time. The data processing device 100 can refer to trends obtained in the past, thereby improving the accuracy of estimating the cause of deterioration.

Fig. 14 is a second diagram showing an example of the distribution of the curve factor and the measurement data of series impedance due to the associative connection of the two parameters in the first example shown in Fig. 11. Figure 15 shows the time series data of the curve factor shown in Figure 14. Figure 15 shows the time-series data of five specimens that are different from the specimen that displayed time-series data on the 12th.

In the time series data shown in Figure 15, the percentage of FF decline after 115 hours has passed is greater than that shown in Figure 12. The FF dropped sharply between 115 hours and 230 hours, and then slowly dropped after 230 hours.

The correlation diagram shown in Figure 14 plots the measurement data of FF and Rs from the start of the test to 920 hours. Figure 14 shows the measurement data of 5 specimens. In Fig. 14, the straight line L2 is a graph obtained by linear approximation of the plot point from the beginning of the test to 115 hours. The straight line L3 is a graph obtained by linear approximation of the plot point from 115 hours to 230 hours. The straight line L4 is a graph obtained by linear approximation of the drawing point after 230 hours.

According to the correlation diagram shown in Fig. 14, the slope of the straight line L2 is closest to the slope of the graph C3 among the graphs C1, C2, and C3. From the beginning of the test to 115 hours, it can be judged that the relationship between the measurement data of FF and Rs is similar to the third correlation. The slope of the straight line L3 is closest to the slope of the figure C2 in the shapes C1, C2, and C3. From 115 hours to 230 hours, it can be judged that the relationship between FF and Rs measurement data is similar to the second correlation. When such a drop in moisture resistance occurs, in the EL image 65 shown in FIG. 8, it can be confirmed that dark portions are generated near each side of the outer shape (rectangular) of the solar battery cell 51. With this EL image 65, it can be grasped from the edge of the solar battery cell 51 that the solar battery cell 51 has deteriorated in moisture resistance.

The slope of the straight line L4 is closest to the slope of the graph C3 among the graphs C1, C2, and C3. After 230 hours, it can be judged that the relationship between FF and Rs measurement data is similar to the third correlation. After 230 hours have passed, it is estimated that the contact resistance of the light-receiving surface electrode 54 uniformly increases in the surface direction. As shown in Figure 15, FF is about 0.72 when 230 hours have passed, and about 0.69 when 920 hours have passed. After 230 hours, the reduction of FF will stop at about 3% to 4%. After 230 hours to 920 hours, the distribution of dark parts in each EL image did not change significantly. Therefore, it was confirmed that the moisture resistance from 230 hours to 920 hours was less deteriorated.

In this way, even when the factors of deterioration are different due to different elapsed time of the test, the estimation processing unit 16 can compare the distribution of the measurement data of the two parameters and the maintained correlation to estimate the cause of deterioration for each elapsed time. In addition, the technician can grasp the trend of the measurement data for each elapsed time. The data processing device 100 can easily comprehend the situation in which the cause of deterioration varies depending on the elapsed time through the correlation diagram.

Fig. 16 is a third diagram showing an example of the distribution of the curve factor and the measurement data of series impedance due to the associative connection of the two parameters in the first example shown in Fig. 11. Figure 17 shows the time series data of the curve factor in the example shown in Figure 16. Figure 17 shows the time series data of five samples that are different from the sample showing time series data on the 12th and 15th sample showing the time series data.

In the time series data shown in Figure 17, the percentage of FF decline after 230 hours has passed is greater than that shown in Figure 12. From the start of the test to 920 hours, the FF of each sample will decrease by about 10% to 15%. In the time-series data shown in Fig. 17, FF is significantly lower than in the case shown in Fig. 12.

The correlation chart shown in Figure 16 depicts the measurement data of FF and RS from the start of the test to 920 hours. Figure 16 shows the measurement data of 5 specimens. In Fig. 16, the straight line L5 is a graph obtained by linear approximation of the plot points from the beginning of the test to the elapse of 115 hours. The straight line L6 is a graph obtained by linear approximation of the drawing points from 115 hours to 230 hours. The straight line L7 is a graph obtained by linear approximation of the drawing point after 345 hours.

According to the correlation diagram shown in Fig. 16, the slope of the straight line L5 is closest to the slope of the graph C3 among the graphs C1, C2, and C3. From the beginning of the test to 115 hours, it can be judged that the relationship between the measurement data of FF and Rs is similar to the third correlation. The slope of the straight line L6 is closest to the slope of the graph C2 among the graphs C1, C2, and C3. From 115 hours to 230 hours, it can be judged that the relationship between FF and Rs measurement data is similar to the second correlation. The slope of the straight line L7 is closest to the slope of the graph C1 among the graphs C1, C2, and C3. After 345 hours, it can be judged that the relationship between the measurement data of FF and Rs is similar to the first correlation.

In the EL image 65 at the start of the test, the entire solar battery cell 51 except for the connection electrode 54B and the connection electrode 55B appeared white. Based on this EL image 65, it was confirmed that the entire part of the solar battery cell 51 other than the connecting electrode 54B and the connecting electrode 55B contributes to light emission. Comparing the EL image 65 from the start of the test to the elapse of 230 hours with the EL image 65 at the start of the test, it was confirmed that dark parts were generated near each side of the outer shape (rectangular) of the solar cell 51. As time passes, the dark portion expands toward the center of the solar cell 51. The appearance of the dark part in the EL image 65 remains the same regardless of the elapsed time. Therefore, it is difficult to identify the cause of the deterioration only in the analysis of the EL image 65.

According to the correlation diagram shown in Figure 16, after 345 hours, the relationship between the measurement data of FF and Rs is similar to that of the first correlation. From such a tendency of the measurement data, it can be estimated that peeling from the semiconductor substrate 53 in all the connection electrodes 55B occurred at the same time. After the end of the test, when the failure analysis was performed by the destruction inspection of the specimen, it was observed that all the connecting electrodes 55B were peeled off, and it was possible to actually verify that the aforementioned estimation was effective.

In this way, even if it is difficult to identify the cause by the analysis of the EL image 65, and it is difficult to confirm the cause without breaking the inspection, the estimation processing unit 16 can compare the distribution of the measurement data of the two parameters and the correlation relationship maintained. The cause of deterioration can be easily estimated.

FIG. 18 is a diagram illustrating a second example of the associative connection between two parameters set by the data processing device 100 shown in FIG. 1. The second example is an example in which the short-circuit current density Jsc and the open circuit voltage Voc are correlated and connected. The setting holding unit 22 holds the setting regarding the related connection of the first parameter Jsc and the second parameter Voc. Figure 18 shows a correlation diagram of the state before plotting the measurement data of Jsc and Voc. In the graph shown in Fig. 18, the vertical axis represents Voc and the horizontal axis represents Jsc.

Fig. 19 shows an example of time-series data of short-circuit current density and open-circuit voltage, which are set by the data processing device 100 shown in Fig. 1 as the parameters related to the connection. The vertical axis of the graph shown in the upper part of Fig. 19 represents the short circuit density Jsc. The vertical axis of the graph shown in the middle part of Fig. 19 represents the open circuit voltage Voc. The lower part of Figure 19 shows an example of time series data for the curve factor FF. The vertical axis of the graph shown in the lower part of FIG. 19 represents FF. The horizontal axis of each graph shown in Fig. 19 represents time. In the second example, as in the first example, the associative link between FF and Rs is set.

Figure 19 shows the time series data of 3 specimens. The time series data will show the measurement data at each time point from the beginning of the test, to 115 hours, 345 hours, and 460 hours.

In the description of the above-mentioned first example shown in Figs. 11 to 17, the decrease in Jsc and Voc was not recognized in the measurement of the output characteristics performed at every set time during the test period. In the second example, it is assumed that Jsc and Voc are decreased in the measurement of output characteristics. According to the graph shown in Fig. 19, Jsc and Voc will decrease with the passage of time from the beginning of the test, like FF.

In FIG. 18, two graphs C4 and C5 showing the relationship between Jsc and Voc when the surface bonding speed on the light-receiving surface of the semiconductor substrate 53 is changed from 10 cm/s to 100000 cm/s are added. The relationship between Jsc and Voc can also be obtained by simulation. In the simulation, as a simulator of the solar battery cell 51, a general one-dimensional semiconductor device simulator is used. FIG. C4 shows the relationship obtained by the simulation of changing only the surface recombination speed of the semiconductor substrate 53 (p-type silicon substrate) in the solar cell unit 51. FIG. C5 shows the relationship when the antireflection film provided on the light-receiving surface of the semiconductor substrate 53 is made thinner than usual, and the surface recombination speed of the p-type silicon substrate is changed. The correlation holding unit 21 holds the correlation function (fourth correlation function) shown in FIG. C4 and the correlation function (fifth correlation function) shown in FIG. C5.

The fifth correlation function is a function representing the correlation between the change in the surface recombination speed at the interface of the semiconductor substrate 53 and the decrease in the thickness of the antireflection film. The deterioration tendency indicated by the fifth correlation function appears when the elution of the antireflection film is proceeding. The anti-reflection film becomes thin due to elution, so that the anti-reflection function of the anti-reflection film decreases. As in Figure C5, the decrease in Jsc is more significant than that in Figure C4, and the thinning of the anti-reflection film makes the decrease in Jsc larger. In addition, the thinning of the anti-reflection film also impairs the passivation effect of the anti-reflection film on the surface of the semiconductor substrate 53. The decrease in the surface passivation effect makes the suppression of carrier recombination on the surface of the semiconductor substrate 53 insufficient, and therefore the decrease in Voc also increases. The correlation holding unit 21 associates and holds the information on the cause of the elution of the anti-reflection film with the fifth correlation function.

Figure 20 shows an example of the distribution of measurement data of short-circuit current density and open-circuit voltage due to the associative connection of the two parameters in the second example shown in Figure 18. Fig. 20 is the correlation diagram shown in Fig. 18 with additional traces of measurement data. For the first parameter Jsc and the second parameter Voc that are set to be linked, the data processing unit 15 generates a combination of the measured value of Jsc and the measured value of Voc in a graph with Jsc as the horizontal axis and Voc as the vertical axis. The correlation diagram of the coordinates. The presentation unit 13 presents the correlation diagram generated by the data processing unit 15. The correlation graph shown in Figure 20 depicts the measured data of Jsc and Voc from the start of the test to 460 hours. Figure 20 shows the measurement data of 3 specimens.

The straight line L8 is a graph obtained by linear approximation of the drawn points from the start of the test to 460 hours. According to the correlation diagram shown in Figure 20, the trace points of the measurement data will be distributed along the graph C5. It can be judged that the relationship between the measurement data of Jsc and Voc is similar to the fifth correlation. The degradation caused by the elution of the anti-reflection film can also be confirmed by the simultaneous decrease of Jsc and Voc in the time series data. With this measurement data and time series data, it can be inferred that the cause of the deterioration is the elution of the anti-reflection film.

Fig. 21 shows an example of the distribution of the measurement data of the curve factor and the series impedance due to the associative connection of the two parameters in the second example shown in Fig. 18. Figure 21 shows a correlation diagram depicting the measurement data of FF and Rs. The straight line L9 is a graph obtained by linear approximation of the drawn points from the start of the test to 460 hours.

According to the correlation diagram in Fig. 21, the slope of the straight line L9 is closer to the slope of the graph C1 than the slope of the graph C3. Therefore, it can be seen that when the anti-reflection film is degraded due to elution, the ratio of the increase in Rs to the decrease in FF is different from the case of the third correlation function, which generally shows the tendency of deterioration of the solar cell module 50. Get bigger. In addition, it can be seen that the relationship of the measurement data when the antireflection film is deteriorated due to elution of the antireflection film is similar to the first correlation function showing the tendency of the increase in series impedance due to the deterioration of the moisture resistance of the entire solar battery cell 51.

The correlation holding unit 21 may also store the result of comparing the relationship between the measurement data of the two parameters that are related and connected with the maintained correlation relationship, thereby accumulating the distribution tendency of the measurement data and the specified reason at any time. The data processing device 100 can improve the accuracy of estimating the cause of deterioration by referring to trends obtained in the past.

The solar battery cell 1 may not use the collector electrode 55A shown in FIG. 5 but a solar battery cell with a PERC (Passivated Emitter AND Rear Cell) structure with a passivation film (insulating film). Under the PERC structure, due to the elution of the insulating film, the phenomenon that Jsc does not decrease but Voc decreases. It is possible to predict the relationship between the measured data of Jsc and Voc when the insulation film deteriorates due to elution, similar to the fourth correlation function that shows the tendency of the anti-reflection film to maintain a normal thickness and change the surface recombination speed . In this manner, the data processing device 100 can also estimate the cause of deterioration based on the prediction of the tendency of the relationship between the cause of deterioration and the measurement data.

Technicians can refer to the maintained correlation as an indicator to determine the cause of deterioration, as well as the meaning expressed by various data such as time series data, measurement data, and image data, and specify the cause of deterioration with high accuracy. The actual performance for identifying the cause of deterioration is stored in the data processing device 100, whereby the data processing device 100 can estimate the cause of the deterioration with high accuracy. Because the cause of deterioration can be easily verified, technicians can specify the cause by simply verifying the cause of deterioration, so measures to improve durability can be immediately reflected in the development design or manufacturing conditions.

According to the first embodiment, the data processing device 100 estimates the cause of the deterioration by comparing the measurement data and the correlation function of the two related parameters, and presents the estimated result. As a result, the data processing device 100 achieves an effect of being able to easily verify the cause of deterioration occurring in the solar cell module 50 in a test for evaluating the durability of the solar cell module 50. [Implementation Type 2]

FIG. 22 is a flowchart showing the steps of the manufacturing method of the solar cell module 50 according to Embodiment 2 of the present invention. The manufacturing process of the solar cell module 50 includes the process of durability evaluation performed by the evaluation system 110. In the second embodiment, the same constituent elements as those in the first embodiment will be marked with the same symbols, and mainly explain the different structures from the first embodiment.

Steps S21 to S23 represent the steps of manufacturing the solar cell module 50. In step S21, the solar cell 51 is produced. In step S21, the surface of the prepared silicon substrate is cleaned, and the cleaned surface forms a texture structure. Next, on the silicon substrate with the texture structure formed, an n-type diffusion layer is formed by the diffusion of n-type impurities. Through the formation of the n-type diffusion layer, a pn junction is formed. Next, pn separation is performed, and the n-type diffusion layer formed on the side surface of the silicon substrate is removed by dry etching. Thereby, the semiconductor substrate 53 is formed.

After the pn is separated, an anti-reflection film (SiN layer) is formed on the side surface of the semiconductor substrate 53 that becomes the light receiving surface. Electrode glue is printed on the light-receiving surface and the back surface of the semiconductor substrate 53 through screen printing. The printed electrode paste is dried, and then the electrodes are fired, thereby forming the light-receiving surface electrode 54 and the back surface electrode 55. In this way, the solar battery unit 51 is produced.

In step S22, the two solar battery units 51 are connected by connecting wires 52 to form a solar battery array. In step S23, the solar cell array in the state of being sandwiched by the transparent resin 56 is further sandwiched by the cover glass 57 and the back sheet 58 to perform lamination processing. In this way, the solar cell module 50 is produced. In addition, in the second embodiment, the steps of manufacturing the solar cell module 50 are not limited to the same steps as the steps S21 to S23. The step of manufacturing the solar cell module 50 only needs to be capable of manufacturing the solar cell module 50 having the function of receiving irradiated light and generating electricity, and it may be a step different from step S21 to step S23.

Next, a test of the solar cell module 50 is carried out. In step S24, the evaluation system 110 performs the measurement of the output characteristics and the EL inspection during the test, and evaluates the durability of the solar cell module 50 produced in steps S21 to S23. The evaluation system 110 evaluates durability through the determination of the presence or absence of deterioration by the calculation unit 14. The data processing device 100 stores measurement data and image data obtained in the test.

When it is determined that there is deterioration (step S25: Yes), in step S26, the data processing device 100 estimates the cause of the deterioration and presents the estimation result. The estimation of the cause of deterioration and presentation of the estimation result will be carried out in the same way as in the first embodiment. By presenting the estimated result, the manufacturing step shown in Fig. 22 ends. When it is determined that there is no deterioration (step S25, No), the manufacturing step shown in FIG. 22 is also ended.

When a degraded evaluation result is obtained, the technician refers to the information of the estimated result presented by the presentation unit 13 to identify the cause of the degradation. The technicians will consider measures such as changes in development and design or adjustment of manufacturing conditions based on the content of the specified cause, and try to improve the cause. In this way, it is possible to try to improve the durability of the solar cell module 50 by identifying the cause of deterioration and improving the identified cause.

According to the second embodiment, the data processing device 100 estimates the cause of the deterioration based on the measurement data obtained from the durability evaluation included in the manufacturing steps of the solar cell module 50. Technicians can specify the cause of deterioration by simply verifying the reason, thereby immediately reflecting the measures to improve durability to the development design or manufacturing conditions. In this way, by simply verifying the cause of the deterioration, it is possible to achieve the effect of simplifying the review until the solar cell module 50 with high durability can be manufactured.

The architecture shown in the above embodiment is an example of the content of the present invention, and can be combined with other known technologies, and part of the architecture can be omitted or changed without departing from the gist of the present invention.

10‧‧‧Control Department 11‧‧‧Memory Department 12‧‧‧Receiving Department 13‧‧‧Reminder Department 14‧‧‧Calculation Department 15‧‧‧Data Processing Department 16‧‧‧Presumption Processing Department 17‧‧‧Related Link Setting Department 18‧‧‧Measurement data storage department 19‧‧‧Image Data Storage Department 20‧‧‧Processing data storage department 21‧‧‧Related Maintenance Department 22‧‧‧Setting holding section 41‧‧‧CPU 42‧‧‧RAM 43‧‧‧ROM 44‧‧‧External memory device 45‧‧‧Communication I/F 46‧‧‧Input device 47‧‧‧Display 48‧‧‧Bus 50‧‧‧Solar battery module 51‧‧‧Solar battery unit 52‧‧‧Connection wiring 53‧‧‧Semiconductor substrate 54‧‧‧Light-receiving surface electrode 54A, 55A‧‧‧ Collector electrode 54B, 55B‧‧‧Connecting electrode 55‧‧‧Inside electrode 56‧‧‧Transparent resin 57‧‧‧Cover glass 58‧‧‧Back plate 61‧‧‧Current source 62‧‧‧Parallel impedance 63‧‧‧Series impedance 64‧‧‧Diode 65‧‧‧EL image 100‧‧‧Data Processing Device 101‧‧‧Output measuring instrument 102‧‧‧EL inspection device 110‧‧‧Evaluation System

FIG. 1 is a block diagram showing the structure of an evaluation system having a data processing device according to Embodiment 1 of the present invention. FIG. 2 is a block diagram showing the hardware structure of the data processing device of Embodiment 1. Fig. 3 is a cross-sectional view of the main part of the solar cell module whose durability has been evaluated by the evaluation system shown in Fig. 1. Fig. 4 is a plan view showing the structure on the light-receiving surface side of the solar battery cells included in the solar battery module shown in Fig. 3. Fig. 5 is a plan view showing the structure of the back side opposite to the light-receiving surface side of the solar battery cells included in the solar battery module shown in Fig. 3. Figure 6 shows the equivalent circuit of the solar cell module shown in Figure 3. Fig. 7 is an example of a graph showing the IV characteristic of the solar cell module shown in Fig. 3. Fig. 8 schematically shows the EL image obtained by the EL inspection device included in the evaluation system shown in Fig. 1. Fig. 9 is a flowchart showing the first operation procedure of the evaluation system shown in Fig. 1. Fig. 10 is a flowchart showing the second operation procedure of the evaluation system shown in Fig. 1. Fig. 11 is a diagram illustrating a first example of the association between two parameters set by the data processing device shown in Fig. 1. Fig. 12 shows an example of time-series data of a curve factor, which is one of the related parameters, set by the data processing device shown in Fig. 1. Fig. 13 is a first diagram showing an example of the distribution of measurement data of the curve factor and series impedance due to the correlation and connection of the two parameters of the first example shown in Fig. 11. Fig. 14 is a second diagram showing an example of the distribution of the curve factor and the measurement data of series impedance due to the associative connection of the two parameters in the first example shown in Fig. 11. Figure 15 shows the time series data of the curve factor shown in Figure 14. Fig. 16 is a third diagram showing an example of the distribution of the curve factor and the measurement data of series impedance due to the associative connection of the two parameters in the first example shown in Fig. 11. Figure 17 shows the time series data of the curve factor in the example shown in Figure 16. Fig. 18 illustrates a second example of the association between two parameters set by the data processing device shown in Fig. 1. Fig. 19 shows an example of time-series data of the short-circuit current density and open-circuit voltage of the parameters set by the data processing device shown in Fig. 1 in relation to the connection. Figure 20 shows an example of the distribution of measurement data of short-circuit current density and open-circuit voltage due to the associative connection of the two parameters in the second example shown in Figure 18. Fig. 21 shows an example of the distribution of the measurement data of the curve factor and the series impedance due to the associative connection of the two parameters in the second example shown in Fig. 18. FIG. 22 is a flowchart showing the steps of the manufacturing method of the solar cell module according to Embodiment 2 of the present invention.

10‧‧‧Control Department

11‧‧‧Memory Department

12‧‧‧Receiving Department

13‧‧‧Reminder Department

14‧‧‧Calculation Department

15‧‧‧Data Processing Department

16‧‧‧Presumption Processing Department

17‧‧‧Related Link Setting Department

18‧‧‧Measurement data storage department

19‧‧‧Image Data Storage Department

20‧‧‧Processing data storage department

21‧‧‧Related Maintenance Department

22‧‧‧Setting holding section

100‧‧‧Data Processing Device

101‧‧‧Output measuring instrument

102‧‧‧EL inspection device

110‧‧‧Evaluation System

Claims (13)

A data processing device that processes measurement data obtained in a test for evaluating the durability of a solar cell module, and includes: a related holding part that maintains and shows the solar cell module for items that cause deterioration of the solar cell module The correlation relationship between the two parameters included in the plural parameters of the output characteristics of the battery module; the estimation processing unit compares the measurement data of the two parameters and the correlation relationship to estimate the cause of deterioration; sets the holding unit to maintain The setting of the association link of the two parameters included in the plural parameters; a measurement data storage section storing the measurement data for each of the plural parameters; and a prompting section presenting the result estimated by the estimation processing section, Wherein the correlation holding section holds a function showing the correlation relationship of the two parameters set with the association connection, and the estimation processing section compares the two parameters associated and connected according to the setting held by the setting holding section The measurement data and the function of, to infer the cause of deterioration. For example, the data processing device described in item 1 of the scope of patent application, wherein: the related holding section links cause information to the function and holds it, wherein the cause information is information indicating the cause of deterioration, and the presumption processing section obtains The function close to the relationship of the measurement data of the two parameters corresponds to the linked cause information, thereby executing the processing required for the estimation. For example, the data processing device described in item 1 or 2 of the scope of patent application further includes: an associative link setting part that executes the setting of the associative link, wherein the setting holding part holds the setting of the associative link set by the associative link setting part . For example, the data processing device described in item 1 or 2 of the scope of patent application further includes: a data processing unit for the two parameters connected in association with the setting held by the setting holding unit Number, process the measurement data, where the data processing part generates a correlation diagram for the first parameter and the second parameter that set the correlation link. The correlation diagram is based on the first parameter as the axis and the second parameter as the A coordinate representing the combination of the measured value of the first parameter and the measured value of the second parameter is drawn on the graph of the axis, and the presentation unit presents the correlation diagram generated by the data processing unit. According to the data processing device described in item 1 or 2 of the scope of patent application, wherein: the setting holding unit holds the setting of the correlation connection of the curve factor as the first parameter and the serial impedance as the second parameter. In the data processing device described in item 5 of the scope of patent application, the correlation holding section holds the function representing the correlation of the variation of the series impedance, that is, the correlation function. The data processing device described in item 5 of the scope of patent application, wherein: the relevant holding portion holds the function representing the correlation between the impedance of the light-receiving surface electrode and the impedance of the back electrode of the solar cell module in the surface direction , Which is the correlation function. According to the data processing device described in item 5 of the patent application, the correlation holding portion holds the function representing the correlation of the change in the contact resistance of the light-receiving surface electrode of the solar cell module, that is, the correlation function. The data processing device described in item 1 or 2 of the scope of patent application, wherein: the setting holding unit holds the setting of the related connection of the short-circuit current density as the first parameter and the open circuit voltage as the second parameter. The data processing device according to claim 9, wherein: the related holding portion holds the change in the surface recrystallization speed of the semiconductor substrate of the solar cell module and the anti-reflection film of the solar cell module This function of the correlation of the thickness reduction is the correlation function. The data processing device described in claim 9, wherein: the correlation holding portion holds the function of the correlation of the change in the surface recrystallization rate of the semiconductor substrate of the solar cell module, that is, the correlation function. A data processing method that uses a data processing device to process the measurement data obtained in a test for evaluating the durability of a solar cell module, including: maintaining and displaying the items that are the cause of deterioration of the solar cell module The correlation between the two parameters included in the multiple parameters of the output characteristics of the solar cell module; by comparing the measurement data of the two parameters and the correlation, the reason for the deterioration is estimated; keeping the complex parameters The setting of the association link of the two parameters included; the measurement data of each of the plural parameters are stored; and the inferred result prompting the cause of deterioration, wherein the two parameters of the association link are kept displayed The correlation function compares the measurement data and the function of the two parameters that are linked in accordance with the maintained setting, thereby inferring the cause of deterioration. A method for manufacturing a solar cell module includes: manufacturing a solar cell module; for matters that cause deterioration of the solar cell module, maintaining two parameters included in a plurality of parameters indicating the output characteristics of the solar cell module The correlation relationship of the two parameters; by comparing the distribution of the measurement data of the two parameters obtained in the test for evaluating the durability of the solar cell module and the maintained correlation relationship, infer the cause of deterioration; The setting of the correlation connection of the two parameters included in the plural parameters showing the output characteristics of the solar cell module; storing the measurement data of each of the plural parameters; and the estimation result that prompts the cause of deterioration, A function showing the correlation relationship of the two parameters of the association connection is maintained, and the measurement data and the function of the two parameters that are associated and connected according to the maintained setting are compared to estimate the cause of deterioration.

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