Thermoelectric coupling-based solar cell temperature analysis method, medium and equipment

Abstract

The invention provides a thermoelectric coupling-based solar cell temperature analysis method, medium and equipment, and the method comprises the steps: carrying out the scanning of impedance maps of different types of batteries, and extracting the parameter data of the batteries under different forward bias voltages; the different types of batteries comprise a single normal battery, a single defective battery, a single battery and a solar battery array; analyzing and processing the battery parameter data to obtain influence factors influencing the temperature of the solar battery; wherein the influence factors comprise one or more of reverse current thermal damage of the battery, a critical condition threshold value of thermal breakdown of the battery and impedance characteristics of the battery. According to the method and the device, the solar cell temperature under different conditions is analyzed, so that factors influencing the cell temperature are known more accurately, and the performance of the solar cell is improved.

Description

Technical Field

[0001] This application belongs to the field of solar power generation equipment technology, and in particular relates to the field of solar cell technology. Background Technology

[0002] In the aerospace field, solar cells serve as the primary energy supply device, and their performance directly impacts the operational efficiency and lifespan of satellites. However, during satellite operation in orbit, the temperature of solar cells is affected by various factors, such as orbital altitude, solar radiation intensity, satellite attitude, and heat dissipation conditions. Changes in these factors lead to temperature fluctuations in the solar cells, thereby affecting their output performance. Therefore, accurately analyzing the temperature changes of solar cells under different conditions has become a key issue in improving the reliability and efficiency of satellite power systems.

[0003] Traditional methods for predicting solar cell temperature often rely on empirical formulas or simplified physical models. While these methods can reflect temperature trends to some extent, they struggle to fully account for the influence of various complex factors, leading to significant errors in the prediction results. Furthermore, with the development of satellite technology, the performance requirements for solar cells are becoming increasingly demanding, and traditional temperature prediction methods are no longer sufficient to meet the sophisticated management needs of modern satellite power systems.

[0004] Therefore, developing a more accurate method for analyzing solar cell temperature is particularly important. This method should be able to comprehensively consider multiple influencing factors and, through advanced data processing technologies and algorithms, achieve real-time monitoring and accurate prediction of solar cell temperature. This will help engineers better understand the factors affecting cell temperature, thereby enabling them to take effective measures to optimize cell design and operating strategies, and improve the overall performance and reliability of satellite power systems. Summary of the Invention

[0005] This application provides a method, medium, and device for analyzing solar cell temperature based on thermoelectric coupling, which is used to analyze the temperature of solar cells under different conditions, so as to more accurately understand the factors affecting the cell temperature and improve the performance of solar cells.

[0006] In a first aspect, embodiments of this application provide a method for analyzing the temperature of solar cells based on thermoelectric coupling, comprising: scanning the impedance spectra of different types of cells to extract cell parameter data under different forward bias voltages; the different types of cells include a single normal cell, a single defective cell, a single cell strip, and a solar cell array; analyzing and processing the cell parameter data to obtain influencing factors affecting the temperature of the solar cell; wherein, the influencing factors include one or more of the following: reverse current thermal damage of the cell, critical threshold condition for cell thermal breakdown, and cell impedance characteristics.

[0007] In one implementation of the first aspect, when the influencing factor is the reverse current thermal damage of the battery, the step of analyzing and processing the battery parameter data to obtain the influencing factors affecting the temperature of the solar cell includes: determining the temperature change, performance change, thermal damage, and thermal breakdown critical value of the single normal cell when applying reverse bias to the single defective cell containing a bypass diode; determining the temperature change, performance change, thermal damage, and thermal breakdown critical value of the single defective cell when applying reverse bias to the single cell containing a bypass diode; determining the voltage allocated to each single cell when applying reverse bias to the single cell under AM0 illumination conditions; and obtaining the reverse charging current in the solar cell array by building an array model.

[0008] In one implementation of the first aspect, when the influencing factor is the critical threshold for battery thermal breakdown, the step of analyzing and processing the battery parameter data to obtain the influencing factor affecting the temperature of the solar cell includes: obtaining the reverse current flowing into the battery, the shunt point volume, and the change between the current flowing into the shunt point and the temperature; obtaining the critical voltage value for battery thermal breakdown; and obtaining the shunt point volume threshold for battery thermal breakdown.

[0009] In one implementation of the first aspect, obtaining the reverse current flowing into the battery, the shunt point volume, and the change between the current flowing into the shunt point and the temperature includes: the battery temperature and the reverse current flowing into the battery have an approximately linear relationship, while the change in the voltage flowing into the battery is approximately a diode curve; the smaller the shunt point volume, the higher the battery temperature, and the temperature corresponding to the inflection point of the shunt point volume is the threshold temperature at which the battery is damaged; the larger the proportion of the current flowing into the shunt point to the total current, the greater the impact on the increase in battery temperature.

[0010] In one implementation of the first aspect, obtaining the critical voltage value for battery thermal breakdown includes: determining the volume of a shunt point that is prone to battery failure, the proportion of current flowing into the shunt point to the total current, and a graph showing the change of the maximum temperature on the battery model with voltage under different bias voltages; and obtaining the critical voltage value for battery thermal breakdown based on the volume of the shunt point, the proportion of current flowing into the shunt point to the total current, and the graph showing the change of the maximum temperature on the battery model with voltage under different bias voltages.

[0011] In one implementation of the first aspect, obtaining the shunt point volume threshold for battery thermal breakdown includes: configuring different numbers of parallel branches and calculating the magnitude of the reverse current flowing into the battery under the corresponding operating conditions according to a preset electrical model; calculating the battery temperature according to a preset thermal model; and, based on the battery temperature, the solar cell temperature threshold, and the number of parallel branches of the battery, inversely calculating the minimum allowable volume of the battery shunt point, which is the shunt point volume threshold for battery thermal breakdown.

[0012] In one implementation of the first aspect, when the influencing factor is the battery impedance characteristics, the step of analyzing and processing the battery parameter data to obtain the influencing factor affecting the temperature of the solar cell includes: establishing an equivalent circuit for fitting the solar cell; obtaining the impedance spectrum of the normal cell and the impedance spectrum of the shunt point cell based on the equivalent circuit; and obtaining the series resistance and parallel resistance of the cell under different forward biases based on each impedance spectrum.

[0013] In one implementation of the first aspect, the method further includes: screening out batteries with degraded performance by comparing the parallel resistance of the battery with that of a standard battery; or comparing battery performance by the slope of the logarithm of the parallel resistance of the battery as a function of the bias voltage.

[0014] In a second aspect, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the solar cell temperature analysis method based on thermoelectric coupling as described in any one of the first aspects of this application.

[0015] Thirdly, embodiments of this application provide an electronic device, the electronic device comprising: a memory storing a computer program; and a processor communicatively connected to the memory, which executes the thermoelectric coupling-based solar cell temperature analysis method as described in any one of the first aspects of this application when the computer program is invoked.

[0016] The thermoelectric coupling-based solar cell temperature analysis method provided in this application analyzes the solar cell temperature under different conditions to more accurately understand the factors affecting the cell temperature and improve the performance of the solar cell. Attached Figure Description

[0017] Figure 1 The flowchart shown is a method for analyzing the temperature of solar cells based on thermoelectric coupling according to an embodiment of this application.

[0018] Figure 2 The diagram shows the temperature and current under normal cell bias in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0019] Figure 3 The image shown is a solar cell emission pattern under a 2.65V bias voltage in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0020] Figure 4 The image shown is a thermal image of a solar cell under a 2.65V bias voltage in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0021] Figure 5The diagram shows the battery IV performance before and after reverse biasing in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0022] Figure 6 The image shown is an IV curve of a solar cell undergoing thermal breakdown in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0023] Figure 7 The diagram shows the reverse current curves flowing into the cell under dark and light conditions in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0024] Figure 8 The diagram shown is a temperature curve of a solar cell under reverse bias in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0025] Figures 9a to 9e The images shown are thermal images under forward bias voltages of 2.50V, 2.55V, 2.60V, 2.65V, and 2.70V, respectively, in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0026] Figures 10a to 10b The images show temperature variation diagrams along the length and width of a solar cell in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0027] Figure 11 The figure shown is an IV performance curve before and after cell damage in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0028] Figures 12a to 12b The shunt volume in the thermoelectric coupling-based solar cell temperature analysis method shown in one embodiment of this application is 600 μm. 3 The split point volume is 200 μm 3 A schematic diagram illustrating the effect of temperature;

[0029] Figures 12c to 12d The diagrams show the effects of a current flowing into the shunt point of 0.22A and a current flowing into the shunt point of 0.40A on temperature in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0030] Figures 13a to 13b The figures are respectively shown as curves of cell temperature change with current and voltage at an orbital altitude of 1300km when parallel mismatch occurs in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0031] Figure 14The graph shown is a curve illustrating the temperature change of the cell as a function of the shunt point volume in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0032] Figure 15 The graph shown is a temperature change curve of the cell temperature as a percentage of the total current flowing into the shunt point in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0033] Figure 16 The 200μm value shown is from a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application. 3 Curve of battery temperature at shunt point versus voltage;

[0034] Figure 17 The flowchart shown is a process for calculating the shunt point volume threshold in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0035] Figure 18 The diagram shows the variation of reverse current with parallel branch data in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0036] Figures 19a to 19b The figures show the minimum allowable shunt point volume curves for different numbers of parallel branches in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application, with the critical temperature being the diode junction temperature of 200°C and the critical temperature being the melting point of Ge of 937°C.

[0037] Figures 20a to 20b The diagrams show the ideal equivalent circuit and the ideal Nyquist curve in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0038] Figure 20c The diagram shown is a schematic diagram of the equivalent circuit of the impedance spectrum in the thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0039] Figures 20d to 20e The diagrams shown are schematic diagrams of the low-bias equivalent circuit and the high-bias equivalent circuit in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0040] Figure 20f The diagram shown is an equivalent circuit diagram of the impedance spectrum of a triple-junction gallium arsenide cell in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0041] Figure 21a The image shown is the impedance spectrum of a normal cell under a bias voltage of 0.6V-2.5V in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0042] Figure 21b The image shown is the impedance spectrum of a normal cell under a bias voltage of 0.9V-2.6V in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0043] Figure 21c The image shown is the impedance spectrum of a normal cell under a bias voltage of 0.6V-0.8V in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0044] Figures 22a to 22b The images show schematic diagrams of the series resistance and parallel resistance as a function of bias voltage in the impedance spectrum of a normal cell in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0045] Figures 23a to 23b The images show schematic diagrams of the series resistance and parallel resistance as a function of bias voltage in the impedance spectrum of the shunt cell in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0046] Figure 24 The diagram shows the IV performance of a solar cell before and after damage in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application.

[0047] Figure 25 The diagram shows the temperature of a solar cell at an orbital altitude of 21,000 km during its orbital period in a solar cell temperature analysis method based on thermoelectric coupling according to an embodiment of this application.

[0048] Figures 26a to 26b The images show schematic diagrams of the simulated temperature and experimental temperature comparison in a thermoelectric coupling-based solar cell temperature analysis method according to an embodiment of this application, when the reverse current is uniformly distributed and when the reverse current is non-uniformly distributed.

[0049] Figure 27 The diagram shown is a structural schematic of an electronic device according to an embodiment of this application. Detailed Implementation

[0050] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed according to different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0051] This application provides a method, medium, and device for analyzing solar cell temperature based on thermoelectric coupling, used to analyze the temperature of solar cells under different conditions, so as to more accurately understand the factors affecting cell temperature and improve the performance of solar cells.

[0052] The following will refer to the appendices in the embodiments of this application. Figure 1 To be continued Figure 5 This application provides a detailed description of the technical solutions in its embodiments. This allows those skilled in the art to understand and implement the thermoelectric coupling-based solar cell temperature analysis method of this embodiment without inventive effort.

[0053] This embodiment provides a method for analyzing the temperature of solar cells based on thermoelectric coupling, wherein the solar cell is preferably a triple-junction gallium arsenide (GaAs) cell. Triple-junction GaAs cells are high-efficiency solar cells widely used in high-end fields such as space stations, satellites, and drones. The photoelectric conversion efficiency of triple-junction GaAs cells far exceeds that of traditional silicon solar cells, with a theoretical maximum efficiency exceeding 50%, and an actual efficiency of around 30%. This means that under the same illumination conditions, triple-junction GaAs cells can generate more electrical energy. This embodiment will subsequently use a triple-junction GaAs solar cell as an example for experimental testing and simulation calculations.

[0054] This embodiment provides a thermoelectric coupling-based solar cell temperature analysis method that analyzes temperature changes in a single normal cell, a single defective cell, a single cell, and a solar cell array due to parallel mismatch. To analyze the positive feedback relationship between the current flowing into the cell and temperature, this embodiment establishes a circuit model in Simulink and corrects the IV characteristic curve for temperature. This embodiment can be used to calculate the magnitude of the backflow current under actual operating conditions.

[0055] Figure 1 The flowchart shown is a process for analyzing solar cell temperature based on thermoelectric coupling, as described in an embodiment of this application. Specifically, as... Figure 1 As shown, the solar cell temperature analysis method based on thermoelectric coupling provided in this application includes the following steps S100 to S200.

[0056] Step S100: Scan the impedance spectrum of different types of batteries to extract battery parameter data under different forward bias voltages; the different types of batteries include single normal cells, single defective cells, single cells, and solar cell arrays.

[0057] Step S200: Analyze and process the battery parameter data to obtain the influencing factors affecting the temperature of the solar cell; wherein, the influencing factors include one or more of the following: reverse current thermal damage of the cell, critical condition threshold for cell thermal breakdown, and cell impedance characteristics.

[0058] The thermoelectric coupling-based solar cell temperature analysis method provided in this embodiment uses electrochemical impedance spectroscopy to scan the impedance spectra of normal and defective cells respectively. It analyzes cell parameter data such as series resistance and parallel resistance extracted from the Nyquist plot under different forward bias voltages. The method then processes these cell parameter data to obtain the factors affecting the solar cell temperature, mainly including:

[0059] 1) The reverse current thermal damage of batteries under various conditions was classified and discussed, exploring the effects of temperature changes, device performance changes, and thermal breakdown thresholds. A single normal battery is prone to thermal runaway in the bias voltage range of [3.0, 3.5] V, and the temperature of a locally defective battery can exceed 1000℃ under certain conditions.

[0060] 2) When the number of parallel branches in the satellite photovoltaic array design does not exceed 22 columns, if the volume of the battery shunt point on the battery string flowing with reverse current is greater than 0.006 mm3, the temperature that will damage the diode can be avoided; if the volume of the battery shunt point on the battery string flowing with reverse current is greater than 10 μm3, the local high temperature point that will damage the Ge layer on the battery can be prevented.

[0061] 3) The equivalent circuit parameters obtained from the impedance spectra of batteries with different defect types are different, with the parallel resistance showing the most significant change.

[0062] 4) Analyze the impedance characteristics of normal batteries and batteries with local shunt point defects. The parallel resistance of the battery with the shunt point is reduced by about 1000 times under low bias voltage, indicating that the formation of the shunt point may be due to the reduction of the parallel resistance at the defect, resulting in the concentration of some current.

[0063] 5) Batteries with degraded performance can be screened by comparing the parallel resistance of the battery with that of a standard battery, or the battery performance can be compared by the slope of the logarithm of the parallel resistance of the battery as a function of bias voltage; the impedance spectrum of a triple-junction gallium arsenide battery can show multiple semi-circular trends under a certain bias voltage, which may correspond to different material interface layers, i.e., different sub-cells.

[0064] The following provides a detailed description of steps S100 to S200 in the thermoelectric coupling-based solar cell temperature analysis method of this embodiment.

[0065] Step S100: The impedance spectra of different types of batteries are scanned to extract battery parameter data under different forward bias voltages; the different types of batteries include single normal cells, single defective cells, single cells, and solar cell arrays.

[0066] Step S200: Analyze and process the battery parameter data to obtain the influencing factors affecting the temperature of the solar cell; wherein, the influencing factors include one or more of the following: reverse current thermal damage of the cell, critical condition threshold for cell thermal breakdown, and cell impedance characteristics.

[0067] In one implementation of this embodiment, when the influencing factor is the reverse current thermal damage of the battery, the step of analyzing and processing the battery parameter data to obtain the influencing factor affecting the solar cell temperature includes:

[0068] 1) When a reverse bias is applied to the single normal cell containing the bypass diode, determine the temperature change, performance change, thermal damage, and thermal breakdown critical value of the single normal cell.

[0069] 2) When the single defective cell is reverse biased with a bypass diode, determine the temperature change, performance change, thermal damage and thermal breakdown critical value of the single defective cell.

[0070] 3) Apply a reverse bias voltage to each cell under AM0 illumination to determine the voltage allocated to each cell;

[0071] 4) Obtain the reverse charging current in the solar cell array by building an array model.

[0072] Specifically, when a reverse bias is applied to the single normal cell containing the bypass diode, the specific implementation method for determining the temperature change, performance change, thermal damage, and thermal breakdown critical value of the single normal cell is as follows.

[0073] In dark conditions, in an indoor environment, the solar cells (including bypass diodes) are reverse biased (the reverse bias range is 2.50V-2.70V).

[0074] At this time, the temperature change of the single normal battery cell is as follows:

[0075] As the bias voltage increases, the battery temperature gradually rises. Bias experiments were conducted on a normal triple-junction gallium arsenide battery. Because the reverse current is small in the bias voltage range of 2.20–2.50V, the battery temperature change is not significant. Therefore, the average battery temperature and current data were recorded for 10 minutes under five different forward bias voltages: 2.50V, 2.55V, 2.60V, 2.65V, and 2.70V. Figure 2 As shown.

[0076] from Figure 2As can be seen, both the battery temperature and current increase with increasing bias voltage. This is because a higher bias voltage results in a larger current flowing into the battery on the volt-ampere characteristic curve, and thus a greater thermal power. At an ambient temperature of 19℃, the battery temperature reaches 31℃ under a 2.70V forward bias. Observing the battery's emission pattern and thermal image, a normal battery emits uniform and bright light under different bias voltages, and the temperature distribution is also very uniform, indicating that the current flows through the battery evenly. Figure 3 and Figure 4 The images shown are the emission pattern and thermal image of the battery under a 2.65V bias voltage, respectively.

[0077] The performance changes of a single normal battery cell are as follows:

[0078] When the reverse bias voltage applied across the battery terminals exceeds a critical value, the battery will thermally break down and fail; when the reverse bias voltage is less than the critical value, the battery's IV performance will change, and after a certain period of time, the IV performance will return to normal levels.

[0079] When a battery is biased at 2.55V, the initial current (when first powered on) is approximately 0.044A. After subjecting the battery to continuous reverse biasing (bias voltage 2.50V-2.65V), the initial current at 2.55V is measured again, and it is 0.062A. After the battery is left to rest for 12 hours, the initial current at 2.55V is measured again, and it is 0.044A. This phenomenon was also observed multiple times in the experiment: the current of the battery after being forward biased for a period of time increases when measured again at the same bias voltage.

[0080] like Figure 5 As shown, by observing the IV characteristic curves of the same battery before and after reverse bias treatment, it can be found that the current of the battery after reverse bias treatment is greater than that of the battery before treatment at the same voltage, and it will basically return to the original normal value after a certain period of time.

[0081] The thermal damage of a single normal battery cell is as follows:

[0082] A forward bias experiment was conducted on a triple-junction gallium arsenide (GaAs) solar cell in the dark state. As the forward bias voltage across the cell gradually increased, the reverse current flowing into the cell also gradually increased. When the reverse bias voltage reached a significant range (greater than the open-circuit voltage of 2.7V), the current flowing into the cell suddenly increased, and the cell changed from a red-light state to a non-light-emitting state within a very short time. Test IV was performed on the non-light-emitting cell, as follows... Figure 6 As shown, the battery's IV curve is almost a straight line, indicating that the battery exhibits resistivity. It is speculated that the battery has been thermally broken down, thus damaging the PN junction.

[0083] The method for obtaining the thermal breakdown critical value of a single normal battery cell is as follows:

[0084] When a battery is subjected to reverse bias, the inflow of reverse current causes a temperature increase. This increased temperature further amplifies the battery's dark saturation current, altering the battery's IV characteristics and increasing the reverse current flowing into the battery, thus continuously raising the temperature. This process is called positive feedback. Simultaneously, heat exchange between the battery and the environment intensifies as the battery temperature rises, limiting the positive feedback process and ultimately stabilizing the battery temperature. When the voltage across the battery reaches a certain value, heat exchange becomes insufficient to control the positive feedback process, and the temperature rapidly rises to a very high value, leading to thermal runaway. This specific value is also known as the critical value for battery thermal breakdown. To simulate the thermal runaway process of a battery under reverse bias, an iterative method is used to calculate the stable reverse current of the battery under different bias voltages.

[0085] from Figure 7 As can be seen, the reverse current increases continuously with the increase of the bias voltage and the slope of the curve increases. When the reverse current flowing in is large enough, the battery temperature will reach a critical value, thus completely damaging the battery.

[0086] like Figure 8 The figure shows the theoretical and experimental data for the temperature corresponding to the reverse bias of the battery, obtained by the iterative method. Experimental data is limited, but the existing data shows a general agreement between the two. The battery temperature rises sharply after 3.0V, indicating that the critical thermal breakdown voltage is in the range of 3.0V to 3.5V.

[0087] In this embodiment, when a bypass diode is applied in reverse bias to the single defective cell, the specific method for determining the temperature change, performance change, thermal damage, and thermal breakdown threshold of the single defective cell is as follows:

[0088] Apply a reverse bias voltage (the reverse bias voltage range is 2.50V-2.70V) to the solar cell (including the bypass diode) with local defects.

[0089] The temperature change of the single defective cell is as follows:

[0090] A normal battery was selected for a destructive experiment. The battery's failure status was determined by the light exposure when the battery was forward-biased. No relevant images were captured here.

[0091] Furthermore, under five different bias voltages, temperature distribution data of the battery under forward bias was collected using a thermal imager, and the thermal images are shown below. Figures 9a to 9e As shown, a high-temperature point appears at the same location on the battery under different bias voltages. The battery temperature was analyzed using SmartView software.

[0092] Comparative analysis of temperature changes along the length and width of the battery under different bias voltages, such as... Figure 10a and Figure 10bAs shown, the temperature at this temperature concentration point increases with increasing bias voltage, and the temperature difference between different bias voltages also increases. We speculate that the battery experiences a local shunt point at the temperature concentration point, causing a concentrated inflow of current, thus raising the battery temperature. The battery with the local high temperature point has the highest temperature. This means that when parallel mismatch occurs, this type of battery will reach a high temperature, further damaging the satellite's power equipment.

[0093] The device performance changes of the single defective cell are as follows:

[0094] A comparison of the IV performance of a battery with localized high temperatures under reverse bias with that before damage is performed, such as... Figure 11 As shown, the IV performance of the damaged battery has decreased.

[0095] No thermal damage was found in the single defective cell within the experimental reverse bias voltage range.

[0096] Unlike normal solar cells, the presumed defect in cells with localized high temperatures is the presence of localized shunt points or leakage current, causing temperature concentration. Because the reverse current does not flow uniformly through the cell, the thermal breakdown critical value of the cell cannot be calculated using iterative methods.

[0097] For mechanistic analysis, analytical techniques such as SEM, which can study at a certain microscale, are needed. Zimmermann prepared a focused ion beam (FIB) cut at the hypothetical defect center of a triple-junction gallium arsenide cell with a shunt point that experienced thermal runaway. He then analyzed the shunt point using scanning electron microscopy and energy-dispersive X-ray diffraction (EDX) and found that the formation of the shunt point was due to the infiltration of silver and carbon elements into the germanium junction and other sub-cell layers. The melting temperature of silver and germanium could be used to deduce that the temperature of the shunt point at this location had reached 1200 K.

[0098] In actual experiments, after some batteries experienced forward breakdown, a focal point appeared on the positive electrode of the back side of the battery. Based on the melting point of Au, the main metallic element on the back side, it can be deduced that the temperature at this point exceeded 1300K. Therefore, for batteries experiencing forward breakdown, the assumption that the temperature concentration was caused by localized current shunt, reaching a localized high temperature capable of damaging the battery, is reasonably plausible.

[0099] The battery actually operates in a vacuum, cold space environment. Based on this, thermal simulation is performed on the battery with a local shunt point to obtain the temperature change of the battery.

[0100] Since most batteries are essentially destroyed at a bias voltage of 3V, this study uses a 3V bias voltage as an example to make corresponding assumptions and models regarding the local shunt point of the battery, simulating the high-temperature conditions that lead to battery failure due to forward breakdown. The finite element analysis software used is Comsol, which overcomes the limitation of Workbench, which can only model down to the 0.01mm scale, allowing for assumptions about the shunt point size down to the nanometer level.

[0101] When a single battery cell is biased at 3V, the initial reverse current, calculated from the IV curve, is 0.613A. Assuming a shunt point exists within the battery, the size of the shunt point and the current flowing into it will significantly affect the battery's final temperature. Comparing the difference between a shunt point volume of 600μm³ and 200μm³, and assuming the current flowing into the shunt point is 0.40A.

[0102] like Figure 12a and Figure 12b As shown, the highest temperature of the battery is at the shunt point; the smaller the shunt point volume, the higher the temperature. When the shunt point volume is 600 μm³, the highest temperature is 282°C; when the shunt point volume is 200 μm³, the highest temperature is 433°C.

[0103] Compare the differences between currents flowing into the shunt point of 0.22A and 0.40A, with a shunt point volume of 600μm. For example... Figure 12c and Figure 12d As shown, under the same operating conditions, when the current flowing into the shunt point increases, the battery temperature will rise accordingly.

[0104] The trends obtained from the two simulation results above indicate that when a battery experiences thermal breakdown, the shunt point in the battery needs to meet two corresponding conditions: a small volume and a large current, in order to reach a high temperature that can damage the battery structure. Considering that positive feedback will occur when the battery is reverse-energized, promoting an increase in the reverse current, we assume that the battery current can reach 1.5A and the size of the shunt point is 200μm. By changing the magnitude of the current flowing into the shunt point, we simulated the battery temperature, and the results are shown in Table 1.

[0105] Table 1. Size of internal heat source in normal battery under different forward bias voltages.

[0106] Total current (A) Current flowing into the shunt point (A) Maximum temperature (°C) 0.613 0.40 484 1.500 0.40 534 1.500 0.80 888 1.500 1.00 1060

[0107] The results in Table 1 show that when the total current is 1.500A and the current flowing into the shunt point is 1.00A, a temperature exceeding 1000℃ will occur, which can damage the battery structure. This situation should be given special attention.

[0108] In this embodiment, the specific implementation of applying a reverse bias voltage to each battery cell under AM0 illumination to determine the voltage allocated to each battery cell is as follows:

[0109] When a reverse bias is applied to a series-connected battery module, theoretically, the voltage received by each individual cell is determined by its IV performance. If the battery string consists entirely of normal cells with identical performance, each cell receives the same voltage. However, if the string contains defective cells with degraded IV performance, the bias voltage of the other normal cells in the series should be greater than that of the defective cells. The voltage drop across each cell can be determined by formula, given the IV performance of each cell.

[0110] The output calculation for a single battery cell is as follows:

[0111]

[0112] In the formula, I1 is the output current of the branch containing a single battery cell, in A; V1 is the output voltage of a single battery cell, in V; I ph1 R represents the photocurrent generated by a single cell, measured in amperes (A). s1 R is the series resistance of a single battery cell, measured in Ω. sh1 I is the parallel resistance of a single battery cell, measured in Ω. o1 I represents the dark saturation current of diode 1 in a single-cell battery, in amperes (A). o2 The dark saturation current of diode 2 in a single-cell battery is expressed in amperes (A). 11 n 21 Here are the quality factors of diodes 1 and 2; T1 is the temperature of the battery, in K; I sc1 This refers to the short-circuit current of the battery, measured in amperes (A); V. bypass This is the forward conduction voltage of the bypass diode, measured in volts (V).

[0113] Assume the total number of series-connected batteries is X, and the total bias voltage is V. total Then it must satisfy

[0114]

[0115] In the formula I 1t Let I be the voltage flowing into each individual cell. Since they are connected in series, the current in each cell is the same. As the bias voltage applied across the series-connected cells changes continuously, I can be solved. 1t With the voltage V of each individual cell 1i .

[0116] The temperature changes of solar cells and the performance changes of solar cell devices are calculated based on the reverse bias voltage and reverse current experienced by each individual cell.

[0117] In this embodiment, the specific implementation of obtaining the reverse charging current in the solar cell array by building an array model is as follows:

[0118] For example, if module A-1 in the solar cell array is in a low voltage state, and other modules are in a high voltage state, analyze the reverse charging current of the other cells to module A-1.

[0119] In a solar cell array, the failure of a single cell (A-1) causes the voltage of its branch to fall below that of other branches, resulting in a reverse current flowing in. The magnitude of the reverse current can be obtained through simulation using Simulink software by building the corresponding array model. The temperature variation of solar cell A-1 and the performance variation of the solar cell device can both be analyzed based on the calculated reverse current and reverse bias voltage of the single cell A-1.

[0120] In one implementation of this embodiment, when the influencing factor is the critical threshold for battery thermal breakdown, the step of analyzing and processing the battery parameter data to obtain the influencing factor affecting the solar cell temperature includes:

[0121] 1) Obtain the reverse current flowing into the battery, the shunt point volume, and the change between the current flowing into the shunt point and the temperature; 2) Obtain the voltage threshold for the battery to undergo thermal breakdown; 3) Obtain the shunt point volume threshold for the battery to undergo thermal breakdown.

[0122] Under parallel mismatch, the battery is subjected to a forward bias. The main factors affecting its temperature include the current flowing into the battery, the volume of the shunt point, and the current flowing into the shunt point. To find the threshold values ​​for each of these influencing factors, a controlled variable method was used. The magnitudes of the variables were adjusted, and the changes in battery temperature were observed. This was done while the battery was in space at an altitude of 300 km.

[0123] In one implementation of this embodiment, obtaining the reverse current flowing into the battery, the shunt point volume, and the change between the current flowing into the shunt point and the temperature includes:

[0124] The relationship between battery temperature and reverse current flowing into the battery is approximately linear, while the relationship with voltage changes flowing into the battery is similar to a diode curve. The smaller the shunt point volume, the higher the battery temperature. The inflection point of the shunt point volume corresponds to the temperature threshold at which the battery is damaged. The larger the proportion of current flowing into the shunt point to the total current, the greater the impact on battery temperature rise.

[0125] When the shunt point size is 5000 μm³, the current flowing into the shunt point accounts for 0.9% of the total current. The magnitude of the current flowing into the shunt point is varied, and the corresponding battery voltage is obtained from the established Simulink electrical model. Taking the maximum battery temperature as the observation object, the reverse current flowing into the battery varies within the range of [0.6, 3.34], and the voltage across the battery varies within the range of [2.77, 3.5]. Figure 13a and Figure 13b As shown.

[0126] from Figure 13a and Figure 13b It can be seen that there is an approximately linear relationship between battery temperature and the reverse current flowing into the battery, while the relationship with the change in voltage flowing into the battery approximates a diode curve. This is mainly because the current generates Joule heat, which is the primary factor causing the battery temperature to rise. Since voltage induces current and follows the law of the IV curve, the voltage-temperature curve also exhibits this trend.

[0127] The volume of the shunt point depends on the cause of defect formation and actual factors, and needs to be obtained through microscopic morphology analysis. In practice, there are many types of shunt point formation, so the volume of the shunt point is discussed. The current flowing into the battery is fixed at 1.3A, and the current flowing into the shunt point accounts for 0.9% of the total current. To ensure uniform heat transfer along the coordinate axes, the shunt point is set as a cube. When the side length of the shunt point increases from 3μm to 18μm in 1μm increments, the highest battery temperature is taken as the dependent variable, and the changes are as follows: Figure 14 As shown.

[0128] from Figure 14 As can be seen, the smaller the shunt volume, the higher the battery temperature. Furthermore, the temperature drops sharply within the shunt volume range of [27, 216] μm³, indicating that the right endpoint of this range represents the threshold temperature at which battery damage occurs. In other words, when the shunt volume reaches this threshold, the battery temperature increases rapidly as the shunt volume decreases, easily reaching the temperature that would damage the battery.

[0129] When the current flowing into the battery and the volume of the shunt point are fixed, the current flowing into the shunt point mainly depends on the resistance of the shunt point. Considering the small size of the shunt point, it is difficult to obtain the resistance value experimentally. Therefore, the proportion of the current flowing into the shunt point to the total current is used instead of Ohm's law calculation. The shunt point size is 5000 μm³, the current flowing into the battery is 1.3 A, and the battery temperature changes with the shunt point current as follows: Figure 15 As shown.

[0130] from Figure 15 As can be seen, there is an approximately linear relationship between temperature and the proportion of current flowing into the shunt point to the total current. This is because the current causes the battery temperature to rise. While the temperature at the shunt point rises, the temperature of the battery model also decreases. In practical applications, the current flowing into the shunt point depends not only on the resistance of the shunt point but also on the distribution of the shunt point at the battery interface and its series / parallel connection with the battery interface. The ratio of the current flowing into the shunt point to the total current roughly illustrates that the larger the current flowing into the shunt point, the greater the impact on the battery temperature rise, and the greater the possibility of failure.

[0131] In one implementation of this embodiment, obtaining the critical voltage value for battery thermal breakdown includes: determining the volume of a shunt point that is prone to causing battery failure, the proportion of current flowing into the shunt point to the total current, and the variation graph of the maximum temperature on the battery model with voltage under different bias voltages; and obtaining the critical voltage value for battery thermal breakdown based on the volume of the shunt point, the proportion of current flowing into the shunt point to the total current, and the variation graph of the maximum temperature on the battery model with voltage under different bias voltages.

[0132] Battery failure due to parallel mismatch stems from the temperature rise caused by reverse current inflow. Therefore, a higher current or voltage flowing into the battery leads to a greater overall temperature increase in the battery model, with the temperature change being approximately linear with the current. Determining the battery failure temperature threshold based solely on current is difficult; voltage is a more suitable choice. Furthermore, shunt points created by defects on the battery accumulate leakage current, forming localized high-temperature points. Increased current flow into the shunt point and smaller shunt point volume both increase the internal heat source, resulting in higher temperatures at the shunt point and further raising the battery's maximum temperature, thus increasing the likelihood of temperature-related failure. Simulation results show that reducing the shunt point volume from 200 μm³ to 20 μm³ causes a sharp temperature increase from 350°C to 550°C. Based on literature, it's possible that shunt point volumes on the order of 200 μm³ are prone to causing battery failure.

[0133] Therefore, the shunt point size is set to 200 μm³, and the current flowing into the shunt point accounts for 0.9% of the total current. The maximum temperature on the battery model varies with voltage under different bias voltages as follows: Figure 16 As shown.

[0134] from Figure 16 As can be seen, the battery temperature increases significantly at the 200μm3 shunt point volume compared to the 5000μm3 shunt point volume. Furthermore, the battery temperature changes approximately linearly with voltage in the range of [3.2, 3.5]V, indicating that the temperature reaches its maximum value at the left end of the range as voltage increases. It can be determined that 3.2V is a crucial inflection point for battery thermal failure. At this point, the reverse current flowing into the battery is approximately 1.82A, and the battery temperature is approximately 850℃.

[0135] The above conclusions can be based on the calculation of the maximum battery temperature when parallel mismatch occurs at an orbital altitude of 300km using finite element analysis software. In actual experiments, due to differences in experimental environment and experimental samples, the battery failure critical point differs from the theoretical calculation result, and it is necessary to analyze it in conjunction with relevant factors.

[0136] In one implementation of this embodiment, obtaining the shunt point volume threshold for battery thermal breakdown includes: configuring different numbers of parallel branches and calculating the magnitude of the reverse current flowing into the battery under the corresponding operating conditions according to a preset electrical model; calculating the battery temperature according to a preset thermal model; and, based on the battery temperature, the solar cell temperature threshold, and the number of parallel branches of the battery, inversely calculating the minimum allowable volume of the battery shunt point, which is the shunt point volume threshold for battery thermal breakdown.

[0137] In practical applications, when the performance of a branch of a solar cell array degrades compared to other normally operating branches, reverse current may flow. The reverse current flowing into that branch is largest when the array is in an open-circuit state. Based on the number of series-connected cells on commonly used satellite solar arrays, the number of cells in series per column is fixed at 20. To calculate the threshold information of the cell shunt point under different operating conditions, different numbers of parallel branches are set, and the magnitude of the reverse current flowing into the cell under the corresponding operating conditions is calculated by the electrical model. Then, the cell temperature is calculated by the thermal model, compared with the silicon diode junction temperature of 200℃ and the solar cell temperature threshold, to deduce the minimum allowable volume of the cell shunt point. The specific process is as follows: Figure 17 As shown.

[0138] To discuss the scenario where a large reverse current causes the battery temperature to reach a level that damages the battery, we assume that the branch carrying the reverse current has experienced the failure of two battery cells, resulting in battery breakdown or short circuit and becoming purely resistive. By using an electrical model built in Simulink, we can calculate the reverse current flowing into the battery string that has experienced battery failure for different numbers of parallel branches, such as... Figure 18 The diagram shows the reverse single current flowing into battery strings with degraded performance in battery branches with 2, 6, 10, 14, 18, and 22 strings.

[0139] from Figure 18 It can be clearly seen that the reverse current increases with the increase of the number of parallel branches, but the rate of increase gradually decreases. From electrical knowledge, we know that the reverse current reaches its maximum value when the voltage across the battery string with degraded performance is equal to the open-circuit voltage of the branch. In actual operating conditions, the presence of degraded battery columns forms a closed loop in the battery array, and the number of parallel branches required to reach the open-circuit voltage across the battery string is close to infinite.

[0140] The shunt point volume threshold of the battery under different reverse currents was calculated using finite element analysis software. The temperature critical values ​​were selected as the junction temperature of the diode (200℃) and the melting point of Ge, the key element in triple-junction gallium arsenide batteries (937℃). The results are as follows: Figure 19a and Figure 19b As shown.

[0141] from Figure 19a and Figure 19bAs can be seen, the more parallel branches there are, the larger the minimum allowable shunt point volume becomes. This is to prevent excessive heat sources from concentrating at the shunt point, causing localized high temperatures in the battery that exceed the critical temperature value. When the critical temperature is the diode junction temperature, the shunt point volume threshold varies more when there are many parallel branches. However, when the critical temperature is the melting point of Ge, although the shunt point volume threshold continues to increase, it remains on the same order of magnitude.

[0142] Therefore, when the number of parallel branches in the satellite photovoltaic array design does not exceed 22 columns, if the volume of the battery shunt point on the battery string flowing with reverse current is greater than 0.006 mm3, the temperature that would damage the diode can be avoided; if the volume of the battery shunt point on the battery string flowing with reverse current is greater than 10 μm3, the local high temperature point that would damage the Ge layer on the battery can be prevented.

[0143] In one implementation of this embodiment, when the influencing factor is the battery impedance characteristic, the step of analyzing and processing the battery parameter data to obtain the influencing factor affecting the solar cell temperature includes:

[0144] 1) Establish the equivalent circuit for fitting the solar cell;

[0145] 2) Obtain the impedance spectrum of the normal battery and the impedance spectrum of the shunt point battery based on the equivalent circuit.

[0146] 3) Obtain the series resistance and parallel resistance of the battery under different forward bias voltages based on the impedance spectra described above.

[0147] In one implementation of this embodiment, the method further includes: screening out batteries with degraded performance by comparing the parallel resistance of the battery with that of a standard battery; or comparing battery performance by the slope of the logarithm of the parallel resistance of the battery as a function of the bias voltage.

[0148] Specifically, in this embodiment, when testing the parameters of a solar cell using electrochemical impedance spectroscopy, the equivalent circuit used to fit the Nyquist curve of the solar cell is generally as follows: Figure 20a As shown, Cp is the composite capacitor, Rp is the composite resistor, and Rs corresponds to the series resistance in the equivalent circuit of the photovoltaic cell. All of these can be calculated from the relevant parameters in the actual equivalent circuit of the photovoltaic cell. Figure 20b The ideal Nyquist curve shown is a semicircle centered on the real axis and with both endpoints on the positive axis. The value of Rs corresponds to the intersection of the left end of the semicircle with the real axis, and the intersection of the right end of the semicircle is the sum of Rs and Rp. The value of Cp can be obtained by curve fitting.

[0149] The equivalent circuit of triple-junction gallium arsenide (GaAs) solar cells mostly uses a dual-diode model. The correspondence between the dual-diode model and the equivalent circuit of the photovoltaic cell impedance spectrum is as follows: Figure 20cAs shown in the diagram. Two diodes are simulated using a pair of parallel resistors and capacitors, where CT is the transition layer capacitance. Diode 1 represents the characteristics of electron-hole pair diffusion, represented by Cd and Rd, which are equivalent, representing the diffusion capacitance and diffusion resistance, respectively. Diode 2 represents the characteristics of electron-hole recombination in the space charge region, represented by Cr and Rr, which are equivalent, representing the recombination capacitance and recombination resistance, respectively. Thus, the total capacitance is the sum of the three capacitances CT, Cd, and Cr, while the total parallel resistance is the parallel value of Rsh, Rd, and Rr. The total series resistance remains Rs. Rsh is the bypass resistance, mainly composed of the following factors: surface leakage current along the cell edge caused by surface contamination; irregular diffusion along dislocations and grain boundaries; or leakage current generated after electrode metallization along microscopic cracks, grain boundaries, and crystal defects forming small bridges. Rs is composed of the surface resistance of the diffusion top region, the bulk resistance of the cell, and the ohmic resistance between the positive and negative electrodes and the metal conductor of the solar cell.

[0150] However, in actual measurement and data analysis, due to the "diffusion effect," CPE is chosen instead of ordinary capacitance C for fitting. Here, CPE does not simply represent capacitance, but rather the electrical double layer at the solid-electrode interface, such as... Figure 20d As shown. However, this equivalent circuit only fits the cell impedance well at low bias voltages. At high bias voltages, especially when the bias voltage is higher than the open-circuit voltage (V≥0.45), the equivalent circuit cannot fit the curve well. At open-circuit voltage or higher, the distortion of the impedance spectrum is due to the asymptotic participation of the net impedance of the p-p+ junction to the solar cell. Therefore, a series inductor is introduced, and the curve after adding the inductor is shown in the figure. Figure 20e As shown. Because of the presence of inductance, the actual parallel and series resistances at low bias voltage cannot be directly read from the intersection of the curve and the real axis; they must be obtained by fitting using Zview.

[0151] In practical applications, considering that a triple-junction gallium arsenide (GaAs) cell is composed of three sub-cells connected in series, each sub-cell is considered to correspond to an RC model. Therefore, the impedance spectrum equivalent circuit model of a triple-junction GaAs cell is as follows: Figure 20f As shown, it is applied to subsequent parameter fitting.

[0152] For the impedance characteristics of normal batteries, triple-junction gallium arsenide (GaAs) batteries have a very wide wavelength range of spectral absorption. Even under experimental light-shielding conditions, photogenerated voltage can still disrupt the impedance test results. Therefore, the bias voltage for impedance testing starts at 0.5V. When the given bias voltage is close to the battery's open-circuit voltage, the test results also fail to form a regular semi-circle; therefore, the bias voltage for testing terminates at 2.5V. Impedance tests were performed on normal triple-junction GaAs batteries using an electrochemical workstation under different forward bias voltages, and the impedance data were analyzed.

[0153] Comparative analysis of the battery's impedance spectrum reveals that the diameter of the semicircle on the Nyquist plot decreases with increasing bias voltage. At higher bias voltages, the battery's impedance spectrum exhibits a flatter semicircle, as shown below. Figures 21a to 21c As shown, the battery may exhibit characteristics of only one sub-cell under this bias range. At lower bias voltages, the impedance spectrum of the battery shows a trend of three semicircles, and this trend increases with increasing bias voltage. Taking the Nyquist plot at a bias voltage of 0.8V as an example, three arcs with different curvatures can be seen. We speculate that one semicircular curve may correspond to the characteristics of one sub-cell of a triple-junction battery, which means that the dominant sub-cell in the battery will change at different frequencies.

[0154] The parameters of the semicircles on the obtained Nyquist plot are fitted, and the changes of the series and parallel resistances with bias voltage are plotted on the graph, as shown below. Figure 22a As shown. Because the resistance of the wires and contacts is unavoidable during the test, the series resistance should be greater than the actual resistance of the battery. The series resistance fluctuates by about 0.4Ω with the increase of the bias voltage, possibly due to systematic errors in the experiment. The parallel resistance changes with the bias voltage as shown... Figure 22b As shown, the resistance decreases with increasing bias voltage, and the decrease is much greater at high bias voltage than at low bias voltage.

[0155] The impedance characteristics of a battery with a shunt point are explained below.

[0156] Using batteries exhibiting shunt points as experimental subjects, AC impedance characteristics were tested under different bias voltages. The shunt-point battery primarily exhibits a localized high-temperature point under forward bias. Comparing its dark-state IV curve with that of a normal battery, the performance of the shunt-point battery shows a decline.

[0157] Because the performance of the shunt battery degrades, its parallel resistance decreases, and its sensitivity to light also decreases, the battery impedance can be measured at low bias voltages. Parameters are fitted and extracted from the battery impedance data under bias voltages of 0.1V-2.5V, such as... Figure 23a and Figure 23b As shown, the series resistance of the battery fluctuates, while the parallel resistance shows a regular decreasing trend with the increase of bias voltage. Furthermore, comparing the parallel resistance value with that of a normal battery reveals that the parallel resistance of the battery at the shunt point under low bias voltage is approximately 1000 times smaller than that of a normal battery.

[0158] Combining impedance spectroscopy and thermal imaging results, it can be analyzed that when defects with small parallel resistance appear inside the battery due to microscopic cracks, grain boundaries, and crystal defects, a portion of the current flows into this point, causing a significant increase in temperature, which can damage the entire battery in severe cases. Simultaneously, the parallel resistance at this defect location within the battery is small, thus significantly reducing the total parallel resistance, which is consistent with the results obtained from impedance spectroscopy. Further analysis of shunt points requires verification at the mechanistic level using other detection methods. However, in practical testing, these two characteristics can be used to sort out batteries with shunt points, reducing their frequency during satellite solar panel assembly.

[0159] The following is a comparison of the simulation and experimental results of this embodiment.

[0160] 1) Battery IV characteristics

[0161] Comparing the IV characteristics output by the battery model built in Simulink software in MATLAB with the measured IV curves of the triple-junction gallium arsenide battery, as follows: Figure 24 As shown, the two curves have a high degree of overlap, indicating that the difference between the simulation and the test is small.

[0162] The open-circuit voltage, short-circuit current, and maximum power point of the battery were selected for comparison, as shown in Table 2. Among them, the relative error between the maximum power point power and the measured value was the largest, at 3.5%, while the errors of the open-circuit voltage and short-circuit current were both less than 0.5%, indicating that the simulation model has high accuracy.

[0163] Table 2 Simulated and measured values ​​of open-circuit voltage, short-circuit current, and maximum power point.

[0164]

[0165] 2) Battery temperature during on-orbit operation

[0166] Calculating the battery's temperature under normal operating conditions in space is fundamental to the analysis of battery parallel mismatch. Temperature data from July 3, 2019 to July 3, 2020, for a BeiDou satellite operating in a medium Earth orbit (M1) were used for verification against the previously established thermal model. The satellite's orbital altitude is 21,000 km, and its orbital period is 12 hours. Because low-temperature data for the satellite's on-orbit temperature is lacking, only the temperature within the satellite's solar-lit area was verified. Figure 25 As shown, the calculated temperature during one orbital period of the satellite around the Earth is compared and verified with the on-orbit temperature data of the solar cells. Ignoring some outliers in the test data, it can be found that the calculated temperature change is close to the tested value, but the magnitude of the temperature differs somewhat, possibly due to certain simplification assumptions in the thermal model. After removing outlier data, the relative error between the theoretically calculated temperature and the actual on-orbit temperature of the satellite is 5.69%.

[0167] 3) Battery temperature under reverse bias

[0168] The temperature data from the forward bias experiment performed on the battery in the laboratory were compared with the simulated temperature data from ANSYS. The simulated temperature values ​​of the battery under uniform and non-uniform reverse current distributions are shown below. Figure 26a and Figure 26b As shown, for the case of non-uniform reverse current inflow, the highest temperature of the battery and the average temperature after removing local high-temperature points are used for verification. When the reverse current is uniformly distributed, the maximum error between the simulated temperature and the experimental temperature is 1.50℃, and the relative error does not exceed 4.8%. When the reverse current is non-uniformly distributed, the maximum error between the simulated temperature and the experimental temperature is 0.78℃, and the relative error does not exceed 1.7%. This indicates that the simulation settings have high accuracy, and a normal temperature model for actual on-orbit application of solar cells can be derived based on this model.

[0169] In summary, this embodiment analyzes the temperature of solar cells under different conditions using a thermoelectric coupling method, and obtains the following technical features and effects:

[0170] (1) A mathematical expression for the energy balance equation was established for the temperature of the solar cell during normal on-orbit operation, and the heat flow and temperature obtained by the cell during one on-orbit operation cycle were calculated. Taking a solar cell with an orbital altitude of 300km as an example, the highest temperature of the cell during the operation cycle was 74℃ and the lowest temperature was -90℃. In order to solve accurately, the thermal resistance in the thickness direction of the cell was further considered, and a two-node temperature equation was established. The highest temperature of the cell during the operation cycle was calculated to be 76.92℃. Based on the established heat dissipation model, the influence of four heat transfer factors—orbital altitude, cell-side absorptivity, substrate-side absorptivity, and substrate-side emissivity—on the cell temperature was calculated, providing a certain reference for the design of satellite-related material properties. Using finite element analysis software, the highest temperature of the cell was simulated to be 77.2℃ and the lowest temperature to be -89.3℃. Overall, the results of the highest cell temperature obtained by the three methods are similar.

[0171] (2) An electrical model of the solar cell was established using a dual-diode equivalent circuit. Based on this, a cell model was established using the Solar Cell module in Simulink simulation software with corresponding parameters. The simulated volt-ampere characteristics were compared with the actual values ​​using root mean square error (RMSE). The calculated RMSE was 0.4099, indicating that the simulation model has high accuracy. The impact of parallel mismatch on the cells was assessed, and the causes of parallel mismatch were analyzed. When parallel mismatch occurs, it may lead to reverse current inflow. Mathematical and simulation models for calculating reverse current were established, and the influencing factors were assessed. A scenario that may lead to a large reverse current was proposed, and the reverse current corresponding to different numbers of parallel cells was calculated.

[0172] (3) A forward bias experiment was designed to simulate the battery situation under parallel mismatch. Temperature data were collected for normal batteries and defective batteries obtained from different destructive experiments under different bias voltages. It was found that defective batteries are more likely to exhibit higher temperatures than normal batteries, especially batteries with local shunt points. Heat dissipation models of batteries under forward bias experiments were established for normal batteries and defective batteries with local shunt points, respectively. The battery simulation settings were then performed in finite element software based on the heat dissipation models. The simulated temperatures were compared with the experimental temperatures, and the maximum errors were 1.50℃ and 0.78℃, respectively, indicating that the heat dissipation models are relatively accurate.

[0173] (4) The thermal damage caused by reverse current in the battery was investigated. Four different conditions were classified and discussed: a single cell with a bypass diode, a cell with a local defect and a bypass diode, a single cell under AM0 illumination, and a solar module operating under normal design conditions (no interconnection, no isolation diode). The effects of temperature changes, device performance changes, and thermal breakdown thresholds were explored. The temperature of a normal single cell rises sharply after 3V, exceeding 300℃, indicating that thermal runaway is likely to occur within the bias range of [3.0, 3.5]V. The temperature of a cell with a local defect can exceed 1000℃ under certain forward bias conditions. Formulas for calculating the voltage of each single cell under forward bias for both single cells and modules under normal design conditions are provided.

[0174] (5) The critical conditions for thermal breakdown of triple-junction gallium arsenide batteries were analyzed, and the effects of conditions such as the current flowing into the battery and the volume of the shunt point on the battery temperature were discussed. When the number of parallel branches in the satellite photovoltaic array design does not exceed 22 columns, the temperature that can damage the diode can be avoided when the volume of the shunt point of the battery in the battery string with reverse current is greater than 0.006 mm3; when the volume of the shunt point of the battery in the battery string with reverse current is greater than 10 μm3, the local high temperature point that can damage the Ge layer on the battery can be prevented.

[0175] (6) The impedance spectra of normal cells and cells with shunt points were scanned using an electrochemical workstation to analyze and extract data such as series resistance and parallel resistance under different forward bias voltages. The results showed that the impedance spectra of normal cells could exhibit a trend of three semicircles under a certain bias voltage, possibly corresponding to different material interface layers, i.e., different sub-cells. The dominant sub-cell in the cell would change at different frequencies. The parallel resistance of the cells decreased with the increase of bias voltage, while the series resistance fluctuated with the change of bias voltage. At the same time, the parallel resistance of the cells with shunt points was smaller than that of the normal cells, which also preliminarily explained the reason for the formation of shunt points. In actual testing, thermal imaging and impedance characteristics were used to sort out cells with shunt points, which could reduce their frequency of occurrence during the satellite solar panel assembly stage.

[0176] The scope of protection of the solar cell temperature analysis method based on thermoelectric coupling described in this application is not limited to the order of steps listed in this embodiment. Any solution implemented by adding, subtracting, or replacing steps in the prior art based on the principles of this application is included within the scope of protection of this application.

[0177] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the solar cell temperature analysis method based on thermoelectric coupling provided in any embodiment of this application.

[0178] In the embodiments of this application, any combination of one or more storage media can be used. The storage medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, RAM, ROM, erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0179] This application also provides an electronic device. Figure 27 The diagram shown is a structural schematic of the electronic device 100 provided in an embodiment of this application. In some embodiments, the electronic device may be a mobile phone, tablet computer, wearable device, in-vehicle device, augmented reality (AR) / virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), or other terminal device. Furthermore, the thermoelectric coupling-based solar cell temperature analysis method provided in this application can also be applied to training datasets, servers, and service response systems based on terminal artificial intelligence. This application does not limit the specific application scenarios of the thermoelectric coupling-based solar cell temperature analysis method.

[0180] like Figure 27 As shown, the electronic device 100 provided in this application embodiment includes a memory 101 and a processor 102.

[0181] The memory 101 is used to store computer programs; preferably, the memory 101 includes various media that can store program code, such as ROM, RAM, magnetic disk, USB flash drive, memory card or optical disk.

[0182] Specifically, memory 101 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory. Electronic device 100 may further include other removable / non-removable, volatile / non-volatile computer system storage media. Memory 101 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of this application.

[0183] The processor 102 is connected to the memory 101 and is used to execute the computer program stored in the memory 101 so that the electronic device 100 executes the solar cell temperature analysis method based on thermoelectric coupling provided in any embodiment of this application.

[0184] Optionally, the processor 102 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0185] Optionally, in this embodiment, the electronic device 100 may further include a display 103. The display 103 is communicatively connected to the memory 101 and the processor 102, and is used to display the relevant GUI interactive interface of the solar cell temperature analysis method based on thermoelectric coupling.

[0186] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A method for analyzing the temperature of solar cells based on thermoelectric coupling, characterized in that, include: Impedance spectra of different types of batteries were scanned to extract battery parameter data under different forward bias voltages; The different types of batteries include single normal cells, single defective cells, single cells, and solar cell arrays; The battery parameter data is analyzed and processed to obtain the influencing factors affecting the temperature of the solar cell; wherein, the influencing factors include one or more of the following: reverse current thermal damage of the cell, critical condition threshold for cell thermal breakdown, and cell impedance characteristics.

2. The solar cell temperature analysis method based on thermoelectric coupling according to claim 1, characterized in that, When the influencing factor is reverse current thermal damage to the battery, the analysis and processing of the battery parameter data to obtain the influencing factors affecting the solar cell temperature includes: When a reverse bias is applied to the single normal cell containing the bypass diode, the temperature change, performance change, thermal damage, and thermal breakdown critical value of the single normal cell are determined. When a bypass diode is applied in reverse bias to the single defective cell, the temperature change, performance change, thermal damage, and thermal breakdown critical value of the single defective cell are determined. A reverse bias voltage is applied to each individual battery under AM0 illumination to determine the voltage allocated to each individual battery. The reverse charging current in the solar cell array is obtained by building an array model.

3. The solar cell temperature analysis method based on thermoelectric coupling according to claim 1, characterized in that, When the influencing factor is the critical threshold for battery thermal breakdown, the analysis and processing of the battery parameter data to obtain the influencing factors affecting the solar cell temperature includes: Obtain the reverse current flowing into the battery, the volume of the shunt point, and the change between the current flowing into the shunt point and the temperature; Obtain the critical voltage value at which the battery will thermally break down; Obtain the shunt volume threshold at which the battery experiences thermal breakdown.

4. The solar cell temperature analysis method based on thermoelectric coupling according to claim 3, characterized in that, The acquisition of the reverse current flowing into the battery, the shunt point volume, and the change between the current flowing into the shunt point and the temperature includes: The relationship between battery temperature and reverse current flowing into the battery is approximately linear, while the relationship with voltage changes flowing into the battery is approximately a diode curve. The smaller the shunt point volume, the higher the battery temperature. The temperature corresponding to the inflection point of the shunt point volume is the threshold for battery damage. The larger the proportion of the current flowing into the shunt point to the total current, the greater the impact on the rise in battery temperature.

5. The solar cell temperature analysis method based on thermoelectric coupling according to claim 3, characterized in that, The threshold voltage at which the battery experiences thermal breakdown includes: Determine the volume of the shunt point that is prone to battery failure, the proportion of the current flowing into the shunt point to the total current, and the graph showing the change of the maximum temperature on the battery model with voltage under different bias voltages. The critical voltage value for thermal breakdown of the battery is obtained based on the volume of the shunt point, the proportion of the current flowing into the shunt point to the total current, and the change of the maximum temperature on the battery model under different bias voltages with voltage.

6. The solar cell temperature analysis method based on thermoelectric coupling according to claim 3, characterized in that, The threshold value for the shunt point where the battery experiences thermal breakdown includes: Configure different numbers of parallel branches and calculate the magnitude of the reverse current flowing into the battery under the corresponding operating conditions based on the preset electrical model; The battery temperature is calculated based on the preset thermal model. Based on the battery temperature, the solar cell temperature threshold, and the number of parallel branches of the battery, the minimum volume that the battery shunt point can allow is deduced, which is the shunt point volume threshold for the battery to undergo thermal breakdown.

7. The solar cell temperature analysis method based on thermoelectric coupling according to claim 1, characterized in that, When the influencing factor is the battery impedance characteristic, the analysis and processing of the battery parameter data to obtain the influencing factors affecting the solar cell temperature includes: Establish an equivalent circuit for fitting the solar cell; Based on the equivalent circuit, the impedance spectrum of the normal battery and the impedance spectrum of the shunt point battery are obtained respectively. The series resistance and parallel resistance of the battery under different forward bias voltages are obtained based on the impedance spectra described above.

8. The solar cell temperature analysis method based on thermoelectric coupling according to claim 7, characterized in that, Also includes: Batteries with degraded performance are screened out by comparing their parallel resistance with that of standard batteries. Alternatively, battery performance can be compared by observing the slope of the logarithm of the battery's parallel resistance as a function of bias voltage.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the solar cell temperature analysis method based on thermoelectric coupling as described in any one of claims 1 to 8.

10. An electronic device, characterized in that, The electronic device includes: A memory that stores a computer program; The processor, which is communicatively connected to the memory, executes the solar cell temperature analysis method based on thermoelectric coupling as described in any one of claims 1 to 8 when calling the computer program.

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