Comprehensive evaluation method for generating efficiency of satellite solar wing under irradiation of high-energy light beam
By using a hierarchical structure model and a dynamic judgment matrix adjustment method, the problem of evaluating the power generation efficiency of satellite solar arrays under high-energy beam illumination was solved, realizing multi-dimensional dynamic evaluation and high-precision consistency verification, thus improving the accuracy and engineering applicability of the evaluation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA ACADEMY OF SPACE TECHNOLOGY
- Filing Date
- 2025-12-15
- Publication Date
- 2026-05-01
AI Technical Summary
Existing technologies struggle to accurately assess the power generation efficiency of satellite solar arrays under high-energy beam illumination, especially in complex space environments where multiple factors are coupled together. Traditional methods suffer from high subjectivity, data scarcity, and insufficient adaptability.
A hierarchical structure model and dynamic judgment matrix adjustment method are adopted. A comprehensive evaluation model for solar panel power generation efficiency is constructed by using the analytic hierarchy process (AHP), including target layer, criterion layer and index layer. The weights are calculated using the judgment matrix and consistency test is performed. The index values are processed by linear standardization to achieve multi-dimensional dynamic evaluation.
It achieves high-precision and reliable assessment of the power generation efficiency of satellite solar arrays under high-energy beam illumination, simplifies the determination of subjective weights and index coupling analysis, and improves the accuracy and engineering applicability of the assessment.
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Figure CN121958730A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of spacecraft energy system performance evaluation technology, specifically involving a quantitative analysis method for satellite solar array power generation efficiency based on a multi-index comprehensive evaluation model, particularly for dynamic evaluation of the power generation performance of satellite solar arrays in complex space environments under high-energy beam illumination. Background Technology
[0002] Solar panels are the core energy system of spacecraft, and their power generation efficiency directly determines the spacecraft's mission endurance. However, the space environment presents challenges such as space debris and micrometeoroid impacts, space radiation, and extreme temperature fluctuations. These factors are not isolated but rather interact through a combination of factors. Therefore, evaluating the power generation efficiency of solar panels requires a comprehensive consideration of multiple influencing factors, rather than focusing solely on a single indicator.
[0003] Early evaluation methods, such as fuzzy comprehensive evaluation and neural network methods, were insufficient in handling "multi-factor coupling" and "hierarchical influence," making it difficult to meet the complex requirements of high-energy beam illumination scenarios. This provided an opportunity for the application of the Analytic Hierarchy Process (AHP).
[0004] Solar panel condition assessment is still in its early stages, and obtaining a large number of samples with clear assessment conclusions is very difficult, requiring the use of expert experience to determine weights. However, expert experience is inevitably subjective, and the weights they determine may distort objective reality. Therefore, based on the expert scores for the importance of each indicator, the Analytic Hierarchy Process (AHP) is used to determine the constant weights for each level of the solar panel. Its rigorous logic is used to "filter" the weights, eliminating subjective factors.
[0005] The Analytic Hierarchy Process (AHP) method is highly applicable for decision-making in high-energy beam illumination scenarios where multiple targets are uncertain. This method combines qualitative and quantitative approaches, incorporating both qualitative analysis from decision-makers and quantitative analysis based on the membership relationships between various indicators. Furthermore, it establishes a systematic indicator structure model through scientific analysis.
[0006] The disadvantages of the fuzzy comprehensive evaluation method are: the determination of weights is subjective, relying on direct weighting by experts and failing to consider the hierarchical relationship between indicators; it is weak in handling hierarchical structure, and fuzzy evaluation is difficult to reflect this hierarchical logic.
[0007] The disadvantages of neural network methods are: strong data dependence, scarce environmental data, and difficulty in supporting model training; poor interpretability, and the inability to trace the model output results, which is not conducive to subsequent optimization of solar array design.
[0008] Furthermore, traditional evaluation methods are not well-suited to atypical data distributions. Solar array on-orbit operational data exhibits small sample characteristics, making it difficult to establish accurate efficiency degradation models using conventional statistical methods. Therefore, there is an urgent need to develop a multi-index comprehensive evaluation method with dynamic weight adjustment capabilities to improve the accuracy and engineering applicability of solar array power generation efficiency assessment. Summary of the Invention
[0009] The technical problem solved by this invention is to overcome the shortcomings of the prior art and provide a comprehensive evaluation method for the power generation efficiency of satellite solar arrays under high-energy beam illumination, thereby solving the problem of accurate evaluation of the power generation efficiency of satellites under high-energy beam illumination interference.
[0010] The solution of this invention is: a comprehensive evaluation method for the power generation efficiency of satellite solar panels under high-energy beam illumination, the method comprising the following steps: S1. Based on the evaluation objectives, establish a hierarchical structure model for the comprehensive evaluation of solar panel power generation efficiency. The hierarchical structure model for the comprehensive evaluation of solar panel power generation efficiency includes an objective layer, a criterion layer, and an indicator layer. The nodes of the criterion layer are the next level below the objective layer, and the indicator layer is the next level below the criterion layer nodes. S2. Construct the judgment matrix of the target layer nodes. Based on the judgment matrix of the target layer nodes, calculate the weight of each node in the criterion layer and perform a consistency check. If the consistency check passes, proceed to step S3; otherwise, adjust the judgment matrix and re-execute step S2. S3. Construct the judgment matrix for each node in the criterion layer. Based on the judgment matrix of each node in the criterion layer, calculate the weight of each node in the index layer and perform a consistency check. If the consistency check passes, proceed to step S4; otherwise, adjust the judgment matrix and re-execute step S4. S4. Calculate the combined weights of each node in the indicator layer; S5. The actual measured indicators are standardized using a linear standardization method to obtain standardized indicator values. Based on the combined weights of each node in the indicator layer, the standardized indicator values are weighted and summed to obtain a comprehensive evaluation result of the power generation efficiency of the satellite solar array under high-energy beam illumination.
[0011] Preferably, the target layer is the top layer, corresponding to the solar panel power generation efficiency evaluation target; The criteria layer is the second layer, which corresponds to the different sub-objectives obtained by decomposing the solar panel power generation efficiency assessment target according to the system structure, including satellite sensing capability, active processing capability, solar panel adjustment capability, and radiation resistance capability; The indicator layer is the lowest layer, containing indicators that can directly acquire data and are related to the criteria layer nodes. Indicators related to satellite sensing capabilities include sensing energy density, sensing energy density accuracy, sensing source elevation angle, sensing source azimuth angle, and sensing source angle accuracy. Indicators related to active processing capabilities include satellite attitude adjustment angular velocity, satellite attitude adjustment angular acceleration, and solar array rotation angular velocity. Indicators related to active processing capabilities include active processing distance, active processing time, energy density, tracking accuracy, and response time. Indicators related to radiation resistance capabilities include radiation resistance energy density, radiation resistance time, and radiation source angle.
[0012] Preferably, the judgment matrix is: in, It is an element relative elements The importance of.
[0013] Preferably, the normalized components of the eigenvectors of the judgment matrix of the target layer node are the weights of each node in the criterion layer; the normalized components of the eigenvectors of the judgment matrix of each node in the criterion layer are the weights of each node in the index layer below each node in the criterion layer.
[0014] Preferably, the power method is used to calculate the eigenvalues and eigenvectors.
[0015] Preferably, the method for adjusting the judgment matrix is as follows: adjust the elements of the judgment matrix according to expert advice, that is, the elements... relative elements The importance of.
[0016] Preferably, the consistency ratio is:
[0017] The consistency index is calculated using the following formula:
[0018] in, To determine the order of a matrix for Random consistency index of the order judgment matrix.
[0019] Preferably, if the consistency ratio If the consistency check is passed, then the consistency check is passed; otherwise, the consistency check is considered to have failed. Preferably, the combined weight of the indicator layer nodes is the weight of all elements in the indicator layer relative to the total target of the target layer, and the criterion layer nodes are... ~ The corresponding weights are respectively , with criteria layer nodes The relevant indicator layer nodes are The corresponding weights are respectively , For criterion layer nodes The number of relevant indicator layer nodes, then the indicator layer nodes The combined weights are: .
[0020] The advantages of this invention compared to the prior art are: (1) This invention combines a hierarchical structure model with a dynamic judgment matrix adjustment method to achieve a multi-dimensional dynamic evaluation of the power generation efficiency of satellite solar arrays under high-energy beam illumination. Compared with the fuzzy comprehensive evaluation method or neural network method in the prior art, this invention simplifies the process of subjective weight determination and index coupling analysis while meeting the high-precision consistency test.
[0021] (2) The combined weight calculation module of the present invention ensures the reliability and engineering applicability of the comprehensive evaluation results in complex spatial environments by synthesizing and normalizing the weights of the criterion layer and the index layer layer layer by layer. Attached Figure Description
[0022] Figure 1 This is a schematic diagram of the weight iterative update process of the comprehensive evaluation method for satellite solar array power generation efficiency under high-energy beam illumination in an embodiment of the present invention.
[0023] Figure 2 This is a block diagram of the consistency verification and adjustment logic in an embodiment of the present invention. Detailed Implementation
[0024] The present invention will be further described in detail below with reference to specific implementation examples. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.
[0025] This invention provides a method for comprehensively evaluating the power generation efficiency of satellite solar panels under high-energy beam illumination, the method comprising the following steps: S1. Based on the evaluation objectives, establish a hierarchical structure model for the comprehensive evaluation of solar panel power generation efficiency. The hierarchical structure model for the comprehensive evaluation of solar panel power generation efficiency includes an objective layer, a criterion layer, and an indicator layer. The nodes of the criterion layer are the next level below the objective layer, and the indicator layer is the next level below the criterion layer nodes. S2. Construct the judgment matrix of the target layer nodes. Based on the judgment matrix of the target layer nodes, calculate the weight of each node in the criterion layer and perform a consistency check. If the consistency check passes, proceed to step S3; otherwise, adjust the judgment matrix and re-execute step S2. S3. Construct the judgment matrix for each node in the criterion layer. Based on the judgment matrix of each node in the criterion layer, calculate the weight of each node in the index layer and perform a consistency check. If the consistency check passes, proceed to step S4; otherwise, adjust the judgment matrix and re-execute step S4. S4. Calculate the combined weights of each node in the indicator layer and perform a consistency check. If the consistency check passes, proceed to step S5; otherwise, adjust the judgment matrix and re-execute step S4. S5. The actual measured indicators are standardized using a linear standardization method to obtain standardized indicator values. Based on the combined weights of each node in the indicator layer, the standardized indicator values are weighted and summed to obtain a comprehensive evaluation result of the power generation efficiency of the satellite solar array under high-energy beam illumination.
[0026] The key points of the invention are described in detail below: 1. Constructing an Alternating Hierarchical Structure (AHP) The hierarchical structure model for comprehensive evaluation of solar panel power generation efficiency includes a target layer, a criterion layer, and an indicator layer.
[0027] The target layer is the top layer, corresponding to the solar panel power generation efficiency evaluation target (root node). The criteria layer is the second layer (intermediate node), which corresponds to the different sub-objectives obtained by decomposing the solar panel power generation efficiency evaluation target according to the system structure, including satellite sensing capability, active processing capability, solar panel adjustment capability, and radiation resistance capability; The indicator layer is the lowest layer (leaf nodes), containing indicators that can directly acquire data and are related to the criteria layer nodes. Indicators related to satellite sensing capabilities include sensing energy density, sensing energy density accuracy, sensing source elevation angle, sensing source azimuth angle, and sensing source angle accuracy. Indicators related to solar array adjustment capabilities include satellite attitude adjustment angular velocity, satellite attitude adjustment angular acceleration, and solar array rotation angular velocity. Indicators related to active processing capabilities include active processing distance, active processing time, energy density, tracking accuracy, and response time. Indicators related to radiation resistance capabilities include radiation resistance energy density, radiation resistance time, and radiation source angle.
[0028] 2. Judgment matrix and weight calculation After establishing a hierarchical structure model for the comprehensive evaluation of solar panel power generation efficiency, a hierarchical progressive method is used to calculate the weights of child nodes and leaf nodes. The specific method is as follows: 2.1 Constructing the judgment matrix The judgment matrix is: in, It is an element relative elements The importance of This corresponds to the number of lower-level nodes associated with the upper-level nodes.
[0029] Taking the target node as an example, the judgment matrix of the target node compares each node in the criterion layer under the target node pairwise (such as comparing the importance of sensing ability, active processing ability, solar array adjustment ability, and radiation resistance), and obtains the judgment matrix of solar cell power generation efficiency evaluation index. The scale is typically 1-9, with specific values shown in the table below.
[0030] Table 1. Scales 1-9 and their meanings
[0031] For elements relative elements The degree of importance is related by the following formula:
[0032] when When, satisfy
[0033] From the two relationships above, we can see that for the judgment matrix... All you need to do is The judgment matrix can be obtained after m comparisons. .
[0034] Satisfying the above two relations, and satisfying A matrix with these properties is called a positive reciprocal matrix.
[0035] 2.2 Calculate weights and eigenvalues. The choice of weights directly reflects the degree of influence of each indicator on the higher-level indicator. Indicator weights refer to the relative importance relationship between indicators at the same node. Theoretically, the weight distribution of a single-level structure can be reduced to obtaining the judgment matrix. The problem of eigenvalues and corresponding eigenvectors. Assumption matrix. The largest eigenvalue is The corresponding feature vector is ,but
[0036] Feature vector The normalized components are used to determine the weights of relevant nodes in the matrix. Methods for finding the largest eigenvalue and eigenvector include the summation method, the root method, and the power method. Among these, the summation and root methods have lower accuracy, while the power method has high accuracy, can be written recursively, and is suitable for computer programming. The specific process for calculating eigenvalues and eigenvectors using the power method is shown below: a. Set initial values for the eigenvectors The initial value can be obtained according to the following formula.
[0037] b. Calculation and normalize it, where ; c. For a pre-defined calculation precision ,like
[0038] Then stop the calculation; otherwise, return to step 2. yes The One component; d. Calculate eigenvalues
[0039] In the formula, It is the number of criterion nodes related to the target node. yes The Each component.
[0040] 2.3 Consistency Check Theoretically, if the judgment matrix A = {a ij For a ij ·a jp =a ip If all true, then A = {a} ij} represents the consistency matrix; if the consistency test passes, then the consistency test fails.
[0041] Due to human error, the judgment matrix It is impossible to completely satisfy a ij ·a jp =a ip To determine whether human error in interpretation is within an acceptable range, it is necessary to calculate the judgment matrix. The consistency ratio, if the consistency ratio If the consistency ratio is 1, the consistency test passes; otherwise, the consistency test fails. The consistency ratio is:
[0042] The consistency index is calculated using the following formula:
[0043] in, To determine the order of a matrix for Random consistency index of the order judgment matrix.
[0044] The calculation methods for the judgment matrix and weights of the third-layer indicator layer, as well as the consistency test, are the same as those for the nodes of the second-layer criterion layer.
[0045] 3. Standardized processing The linear standardization method is used to standardize the actual measured indicators according to their range, dimensions, lower limit and upper limit of quantification value, so as to obtain standardized indicator values.
[0046] 4. Calculate the combined weight of the bottom-level nodes. To determine the weights of all elements at each level of the hierarchical structure relative to the overall objective, it is necessary to synthesize and appropriately combine the calculation results from the previous level to obtain the relative importance weights of each element relative to the objective of the previous level. Using the Analytic Hierarchy Process (AHP), a judgment matrix is constructed, and its largest eigenvalue and corresponding eigenvector are calculated to determine the weight coefficients of each indicator. The consistency of the calculation process is then checked. The calculation is iteratively performed layer by layer from the top to the bottom, ultimately obtaining the ranking weights of the elements at each lowest level and the overall consistency check results of the hierarchical model.
[0047] This method allows us to determine the priority of decision-making options and the reliability of the entire evaluation system. The calculation steps include the following: The combined weight of the indicator layer nodes is the weight of all elements in the indicator layer relative to the total target of the target layer. The criterion layer nodes are... ~ The corresponding weights are respectively , with criteria layer nodes The relevant indicator layer nodes are The corresponding weights are respectively , For criterion layer nodes The number of relevant indicator layer nodes, then the indicator layer nodes The combined weights are: .
[0048] By applying the Analytic Hierarchy Process (AHP), we can obtain the priority ranking weights of each decision option relative to the overall goal, and give the overall consistency index of all judgments in the entire hierarchical structure on which this combined ranking weight is based, and then make a decision.
[0049] Power generation efficiency is the result of the combined effect of multiple factors. Based on this characteristic, the weighted average operator is selected as the composition function, which can balance the weight of each factor and take into account the impact of each factor on the overall index. It is particularly suitable for the comprehensive evaluation of the overall index. Example: 1. First, establish and construct an Assessment Hierarchical Structure (AHP) based on the assessment objectives. like Figure 1 As shown, the evaluation indicators for power generation efficiency include: sensing capability, adjustment capability, radiation resistance capability, and active processing capability.
[0050] Satellite sensing capabilities, active processing capabilities, solar array adjustment capabilities, and radiation resistance capabilities are the criteria layer nodes; the criteria layer nodes are the next layer nodes below the target layer nodes. Sensing energy density, sensing energy density accuracy, sensing source elevation angle, sensing source azimuth angle, and sensing source angle accuracy are the next layer nodes of the satellite sensing capability nodes. Satellite attitude adjustment angular velocity, satellite attitude adjustment angular acceleration, and solar array rotation angular velocity are the next level nodes below the solar array adjustment capability node; Active processing range, active processing time, energy density, tracking accuracy, and response time are the next level nodes in the active processing capability node; Radiation resistance energy density, radiation resistance time, and radiation source angle are the next level nodes in the radiation resistance capability node.
[0051] 2. Construct the second-level judgment matrix, calculate the weights, and perform consistency checks. (1) Judgment matrix of solar cell power generation efficiency evaluation index Table 1. Values of elements in the solar cell power generation efficiency evaluation index matrix.
[0052] The values in the table above can be determined based on expert opinions.
[0053] Eigenvalue calculation results =4.0685 The feature vector is = [0.1222 0.2976 0.5232 0.0570] T ; The results show that, in the evaluation of the protective effectiveness of satellite solar panels in terms of power generation efficiency, the protection effect is most prominent in "radiation resistance", accounting for about 52.32%.
[0054] (3) Consistency Indicators In this embodiment, the consistency index for:
[0055] Let be the order of the matrix. To meet the consistency requirements across different orders, random consistency indices for matrix orders 1-10 are needed. As shown in the table below.
[0056] Average random consistency index
[0057] Calculate the consistency ratio
[0058] Consistency ratio Passing the consistency test, such as Figure 2 As shown.
[0059] 3. Construct the third-layer indicator judgment matrix, calculate the weights, and perform consistency checks. (1) Judgment matrix a. Perception Ability Indicator Layer
[0060] b. Adjusting the capability indicator layer
[0061] c. Radiation resistance index layer
[0062] d. Proactive processing capability indicator layer
[0063] (2) Calculate weights and eigenvalues
[0064] (3) Consistency check
[0065] The consistency index CR < 0.1, and the index-level judgment matrix passes the consistency test.
[0066] 4. Indicator Standardization The linear standardization method was used to standardize each indicator in the indicator layer. The original values and standardized values of the indicators are shown in the table below.
[0067]
[0068] 4. Calculate the combined weights of elements in each layer. The calculation results of the combined weights are shown in the table below. Considering the weights of each indicator in the combined criteria layer and indicator layer, the current comprehensive power generation efficiency score is 83.75.
[0069]
[0070] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solutions of the present invention by utilizing the methods and techniques disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the protection scope of the technical solutions of the present invention.
Claims
1. A comprehensive evaluation method for the power generation efficiency of satellite solar arrays under high-energy beam illumination, characterized in that... Includes the following steps: S1. Based on the evaluation objectives, establish a hierarchical structure model for the comprehensive evaluation of solar panel power generation efficiency. The hierarchical structure model for the comprehensive evaluation of solar panel power generation efficiency includes an objective layer, a criterion layer, and an indicator layer. The nodes of the criterion layer are the next level below the objective layer, and the indicator layer is the next level below the criterion layer nodes. S2. Construct the judgment matrix of the target layer nodes. Based on the judgment matrix of the target layer nodes, solve the weight of each node in the criterion layer and perform a consistency check. If the consistency check passes, proceed to step S3. Otherwise, adjust the judgment matrix and re-execute step S2; S3. Construct the judgment matrix of each node in the criterion layer. Based on the judgment matrix of each node in the criterion layer, calculate the weight of each node in the index layer and perform a consistency check. If the consistency check passes, proceed to step S4. Otherwise, adjust the judgment matrix and re-execute step S4; S4. Calculate the combined weights of each node in the indicator layer; S5. The actual measured indicators are standardized using a linear standardization method to obtain standardized indicator values. Based on the combined weights of each node in the indicator layer, the standardized indicator values are weighted and summed to obtain a comprehensive evaluation result of the power generation efficiency of the satellite solar array under high-energy beam illumination.
2. The method for comprehensively evaluating the power generation efficiency of a satellite solar array under high-energy beam illumination as described in claim 1, characterized in that, The target layer is the top layer, corresponding to the solar panel power generation efficiency evaluation target; The criteria layer is the second layer, which corresponds to the different sub-objectives obtained by decomposing the solar panel power generation efficiency assessment target according to the system structure, including satellite sensing capability, active processing capability, solar panel adjustment capability, and radiation resistance capability; The indicator layer is the lowest layer, containing indicators that can be directly obtained from the criteria layer nodes. Indicators related to satellite sensing capabilities include sensing energy density, sensing energy density accuracy, sensing source elevation angle, sensing source azimuth angle, and sensing source angle accuracy. Indicators related to active processing capabilities include satellite attitude adjustment angular velocity, satellite attitude adjustment angular acceleration, and solar array rotation angular velocity; Indicators related to active processing capability include active processing distance, active processing time, energy density, tracking accuracy, and response time; indicators related to radiation resistance capability include radiation resistance energy density, radiation resistance time, and radiation source angle.
3. The method for comprehensively evaluating the power generation efficiency of a satellite solar array under high-energy beam illumination as described in claim 1, characterized in that, The judgment matrix is: in, It is an element relative elements The importance of.
4. The method for comprehensively evaluating the power generation efficiency of a satellite solar array under high-energy beam illumination as described in claim 1, characterized in that, The normalized components of the eigenvectors of the judgment matrix of the target layer nodes are the weights of each node in the criterion layer. The normalized components of the eigenvectors of the judgment matrices of each node in the criterion layer are the weights of each node in the index layer under each node in the criterion layer.
5. The method for comprehensively evaluating the power generation efficiency of a satellite solar array under high-energy beam illumination as described in claim 3, characterized in that, The power method is used to calculate eigenvalues and eigenvectors.
6. The method for comprehensively evaluating the power generation efficiency of a satellite solar array under high-energy beam illumination as described in claim 3, characterized in that, The method for adjusting the judgment matrix is as follows: adjust the elements of the judgment matrix according to expert advice, that is, the elements... relative elements The importance of.
7. The method for comprehensively evaluating the power generation efficiency of a satellite solar array under high-energy beam illumination as described in claim 3, characterized in that, The consistency ratio is: The consistency index is calculated using the following formula: in, To determine the order of a matrix for Random consistency index of the order judgment matrix.
8. The method for comprehensively evaluating the power generation efficiency of a satellite solar array under high-energy beam illumination according to claim 7, characterized in that, If the consistency ratio If the consistency test is passed, then the consistency test is passed; otherwise, the consistency test is considered to have failed.
9. The method for comprehensively evaluating the power generation efficiency of a satellite solar array under high-energy beam illumination according to claim 7, characterized in that, The combined weight of the indicator layer nodes is the weight of all elements in the indicator layer relative to the total target of the target layer. The criterion layer nodes are... ~ The corresponding weights are respectively , with criteria layer nodes The relevant indicator layer nodes are The corresponding weights are respectively , For criterion layer nodes The number of relevant indicator layer nodes, then the indicator layer nodes The combined weights are: .