Energy storage dielectric material interface charge inversion and performance parameter evaluation method and system
Patent Information
- Application Number
- CN202611144310.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-30
- Publication Date
- 2026-09-18
AI Technical Summary
[0004]有鉴于此，本发明的目的在于提供一种储能电介质材料界面电荷反演与性能参数评估方法及系统，以解决传统储能电介质材料评价主要依赖介电常数、介电损耗、击穿强度、P-E电滞回线、储能密度和充放电效率等宏观参数，难以反映界面电荷空间分布、局部电荷积累、低响应区域、击穿薄弱区及性能退化来源的问题
（1）本发明将阵列化电响应采集、界面电荷反演、空间特征提取和储能性能评价连接为完整技术路径，使储能电介质材料评价不再局限于宏观介电参数，而是能够反映界面电荷空间分布和局部失效风险。
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Abstract
Description
Technical Field
[0001] This invention belongs to the field of energy storage dielectric material testing technology, and relates to a technical solution for obtaining the interface charge distribution of energy storage dielectric materials through arrayed electrical signal acquisition and physical constraint inversion, and further evaluating polarization uniformity, interface charge stability, local leakage risk, breakdown weak area and energy storage performance degradation. Background Technology
[0002] Energy storage dielectric materials are key functional materials in thin-film capacitors, pulse power devices, high dielectric constant composite materials, flexible energy storage devices, and high-voltage insulated energy storage structures. Their energy storage density, charge-discharge efficiency, breakdown strength, cycle stability, and long-term service reliability are closely related to charge accumulation, polarization response, trap distribution, and local leakage channels within and at the material's interface.
[0003] Current performance evaluation of energy storage dielectric materials typically relies on dielectric constant testing, dielectric loss testing, breakdown strength testing, PE hysteresis loop testing, leakage current testing, and charge / discharge efficiency testing. While these methods can obtain macroscopic energy storage parameters, they often fail to reflect the spatially uneven distribution of interfacial charges and struggle to pinpoint weak regions leading to localized leakage, premature breakdown, or efficiency degradation. For multilayer dielectrics, polymer-based composite dielectrics, ceramic-filled composite dielectrics, and flexible energy storage films, interfacial polarization, filler agglomeration, micro-defects, and localized electric field distortions significantly impact energy storage performance, making it difficult to accurately determine the sources of performance degradation based solely on overall electrical indicators. Existing methods such as surface potential imaging, Kelvin probe microscopy, dielectric spectroscopy, or finite element simulation can characterize charge behavior or electric field distribution to some extent, but they suffer from problems such as complex testing processes, insufficient in-situ accuracy, limited spatial coverage, high sample preparation requirements, and difficulty in coupling with actual charge / discharge or mechanical contact states. Therefore, there is an urgent need for a method capable of inverting the interfacial charge distribution of energy storage dielectric materials over a large area and further transforming the inversion results into energy storage performance parameter evaluation results. Summary of the Invention
[0004] In view of this, the purpose of the present invention is to provide a method and system for interface charge inversion and performance parameter evaluation of energy storage dielectric materials, so as to solve the problem that the evaluation of traditional energy storage dielectric materials mainly relies on macroscopic parameters such as dielectric constant, dielectric loss, breakdown strength, PE hysteresis loop, energy storage density and charge and discharge efficiency, which are difficult to reflect the spatial distribution of interface charge, local charge accumulation, low response region, breakdown weak region and the source of performance degradation.
[0005] This invention is based on the principle that arrayed electrical signal measurement can collect material interface potential, charge response or induced electrical signals from multiple spatial locations, establishes the physical mapping relationship between array response and interface charge distribution, and obtains a two-dimensional interface charge map through a stable inversion method, and analyzes the local polarization inhomogeneity, interface trap activity, leakage risk and breakdown weak area of energy storage dielectric materials.
[0006] To achieve the above objectives, the present invention provides a method for interface charge inversion and performance parameter evaluation of energy storage dielectric materials, comprising: An arrayed test structure for energy storage dielectric materials, including arrayed sensing electrodes, was constructed. The energy storage dielectric material under test was brought into contact with the arrayed sensing electrodes, and an excitation was applied to induce the energy storage dielectric material under test to generate an interface charge response. Multi-channel electrical response signals at different spatial locations of the energy storage dielectric material under test are acquired by arrayed sensing electrodes, and array response data is obtained by preprocessing the multi-channel electrical response signals. A positive mapping model between array response and interface charge density distribution is established; using array response data as input, a two-dimensional interface charge density distribution map is obtained by solving the interface charge inversion algorithm, with physical constraints applied during the solution process; Spatial distribution features are extracted from the two-dimensional interface charge density distribution map. Based on these features, a parameterized evaluation model for energy storage performance is established, and the performance parameter evaluation results are output.
[0007] Furthermore, establishing a positive mapping model between the array response and the interface charge density distribution involves dividing the interface of the energy storage dielectric material under test into N charge units, with the interface charge density vector represented as follows: The positive mapping model between the array response and the interface charge density distribution is expressed as:
[0008] in, For the response matrix, For noise terms, The response is the array response; the elements of the response matrix are the response coefficients between the electrodes and charge units in the arrayed inductive electrodes.
[0009] Furthermore, using the array response data as input, the two-dimensional interface charge density distribution map is obtained by solving the interface charge inversion algorithm, including: Based on the forward mapping model and physical constraints, a regularized objective function with physical constraints is constructed. The physical constraints include smoothness constraints, boundary preservation constraints, non-negativity constraints, and sparsity constraints. Smoothness constraints are used to suppress charge map fluctuations caused by random noise. Non-negativity constraints are used to maintain the physical rationality of the inverted charge distribution. Boundary preservation constraints are used to retain the spatial boundary characteristics caused by material defects, interface abrupt changes, local leakage, or breakdown weak areas. Sparsity constraints are used to constrain the spatial concentration of interface charge distribution and suppress non-realistic charge diffusion caused by measurement noise or model errors. The two-dimensional interface charge density distribution map is iteratively updated through this objective function. When the iteration stopping condition is met or the number of iterations reaches the preset upper limit, the iteration stops and the two-dimensional interface charge density distribution map is output.
[0010] The objective function is expressed as:
[0011] In the formula, The interface charge distribution to be inverted. The response matrix is determined by the electrode array geometry and dielectric parameters. These are the constraint weighting coefficients.
[0012] Furthermore, spatial distribution features are extracted from the two-dimensional interface charge density distribution map. These spatial distribution features include the average interface charge density, polarization uniformity coefficient, low response region area ratio, and boundary gradient.
[0013] Furthermore, establishing a parameterized evaluation model for energy storage performance based on spatial distribution characteristics includes normalizing the extracted spatial distribution characteristics and weighting them according to preset weights to obtain performance parameters; among which, the performance parameters include polarization capability parameters, polarization uniformity parameters, breakdown weak area parameters, and local leakage risk parameters. Further weighted calculations were performed on each performance parameter to obtain the local defect risk index and the comprehensive performance score.
[0014] Furthermore, the method also includes classifying the risk level of the energy storage dielectric material under test based on the local defect risk index and the comprehensive performance score. Specifically, the energy storage dielectric material under test is classified into low-risk, medium-risk, or high-risk levels according to the local defect risk index and the comprehensive performance score.
[0015] Furthermore, the arrayed test structure includes a fixed base, arrayed sensing electrodes, an insulating isolation layer, a loading component, and a signal lead-out terminal.
[0016] An arrayed sensing electrode is positioned above a fixed base, an insulating layer is positioned between the arrayed sensing electrode and the fixed base, a loading component is positioned above the arrayed sensing electrode, and a signal output terminal is connected to the arrayed sensing electrode; the energy storage dielectric material to be tested is fixed between the arrayed sensing electrode and the loading component.
[0017] Specifically, electric field polarization-release, charge-discharge excitation, contact separation excitation, or mechanical disturbance excitation are applied to the energy storage dielectric material under test by loading components to induce the generation of interface charge response in the energy storage dielectric material under test.
[0018] Furthermore, the preprocessing of the multi-channel electrical response signal includes baseline correction, filtering, and normalization.
[0019] Furthermore, the arrayed sensing electrodes can be two-dimensional electrode arrays, flexible electrode arrays, or scanning electrode arrays.
[0020] Another aspect of the present invention provides a system for interface charge inversion and performance parameter evaluation of energy storage dielectric materials for the above-described method. The system includes an arrayed test structure, a signal preprocessing module, an interface charge inversion module, a spatial feature extraction module, and a performance parameter evaluation module.
[0021] The signal preprocessing module is used to acquire the multi-channel electrical response signal output by the arrayed test structure and preprocess it to obtain the array response data; the interface charge inversion module receives the array response data and generates a two-dimensional interface charge density distribution map; the spatial feature extraction module extracts the spatial distribution features from the two-dimensional interface charge density distribution map; and the performance parameter evaluation module outputs the energy storage performance parameters and the risk level of the energy storage dielectric material under test based on the spatial distribution features.
[0022] The beneficial effects of this invention are as follows: (1) This invention connects arrayed electrical response acquisition, interface charge inversion, spatial feature extraction and energy storage performance evaluation into a complete technical path, so that the evaluation of energy storage dielectric materials is no longer limited to macroscopic dielectric parameters, but can reflect the spatial distribution of interface charge and local failure risk.
[0023] (2) By establishing a positive mapping relationship between array response and interface charge density distribution and introducing regularization constraints for inversion, this invention can improve the stability and noise resistance of interface charge map reconstruction under limited sampling channels.
[0024] (3) The present invention transforms the local charge accumulation, low response region and breakdown weak region in the interface charge map into quantifiable indicators by using parameters such as polarization uniformity coefficient, low response region area ratio, boundary gradient index and local defect risk index.
[0025] (4) This invention is applicable to polymer energy storage films, ceramic filler / polymer composite media, flexible energy storage media, multilayer capacitor dielectric layers and other energy storage dielectric materials, and can be used for material screening, process optimization, aging evaluation and failure risk location.
[0026] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description
[0027] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 The flowchart of the method for interface charge inversion and performance parameter evaluation of energy storage dielectric materials provided by the present invention is shown.
[0028] Figure 2 This is a schematic diagram of the overall structure of the array-based test structure for energy storage dielectric materials.
[0029] Figure 3 This is a schematic diagram illustrating the principle of charge generation and electron flow during the contact-separated TENG excitation process.
[0030] Figure 4 This is a schematic diagram of a multi-channel signal sampling circuit.
[0031] Figure 5 This is a schematic diagram of the preprocessing flow for multi-channel response signals.
[0032] Figure 6 This is a schematic diagram of the interface charge distribution inversion algorithm.
[0033] Figure 7 This is a comparison of the effects of different inversion constraints on boundary preservation and noise suppression of the interface charge map.
[0034] Figure 8 This is a data map for extracting spatial distribution features from the interface charge distribution map.
[0035] Figure 9 This diagram illustrates the parameterized evaluation and risk level output for energy storage performance.
[0036] Figure 10 This is a comparative data chart of interface charge diagrams and performance scores for different energy storage dielectric materials under different aging stages or different cycle numbers.
[0037] Reference numerals: 1-Fixed base, 2-Arrayed sensing electrodes, 3-Insulating layer, 4-Dielectric material to be tested, 5-Loading component, 6-Signal output terminal. Detailed Implementation
[0038] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.
[0039] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.
[0040] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.
[0041] like Figure 1 As shown, this is a method for interface charge inversion and performance parameter evaluation of energy storage dielectric materials according to an embodiment of the present invention. The method is described as follows: 1. Construct an array-based test structure for energy storage dielectric materials, place the energy storage dielectric material to be tested at the corresponding position of the array-based induction electrode, and induce the material to generate interface charge response through electric field polarization-release, charge-discharge excitation, contact separation excitation or mechanical disturbance excitation.
[0042] Among them, the arrayed test structure is as follows Figure 2 As shown, it includes a fixed base 1, an arrayed induction electrode 2, an insulating layer 3, a dielectric material to be tested 4, a loading component 5, and a signal output terminal 6.
[0043] The fixed base 1 supports and positions each functional layer, ensuring the flatness of the device structure and repeatability during testing. The arrayed sensing electrodes 2 are positioned above the fixed base 1 and collect induced charge, potential, or voltage responses at different spatial locations through a regular or partitioned array. An insulating layer 3 is positioned between the arrayed sensing electrodes 2 and the fixed base 1 to prevent direct short-circuiting between the electrodes and external metal, while maintaining local electric field coupling. The energy storage dielectric material 4 under test is placed above the arrayed sensing electrodes 2 and can be a polymer thin film, composite dielectric thin film, ceramic-filled polymer dielectric, flexible energy storage dielectric, or multilayer dielectric structure. The arrayed sensing electrodes 2 can be positioned below the energy storage dielectric material 4, or, depending on the material form, packaging method, or testing requirements, on the side, back, or both sides of the energy storage dielectric material 4, to accommodate different test objects such as planar thin films, wound structures, stacked structures, and flexible devices. The loading component 5 is used to apply controllable contact separation excitation to the energy storage dielectric material 4 under test, and can adjust the contact pressure, separation distance, contact frequency, sliding displacement or loading period to induce interface charge response under different operating conditions. The signal output terminal 6 is electrically connected to the arrayed induction electrodes 2 and is used to output the electrical signals generated by each electrode channel to the multi-channel sampling circuit to provide raw data for subsequent signal preprocessing, interface charge distribution inversion and energy storage performance parameter evaluation.
[0044] The multi-channel sampling circuit includes an electrode array interface, a channel selection module, a charge / voltage conversion module, a filtering and amplification module, an analog-to-digital conversion module, a synchronization clock module, and a data processing unit. For example... Figure 4 As shown, the electrode array interface is used to connect each independent sensing electrode; the channel selection module is used to realize multi-channel synchronous sampling or time-division scanning; the charge / voltage conversion module is used to convert weak induced charge or potential signals into processable voltages; the filtering and amplification module is used to improve the signal-to-noise ratio; the analog-to-digital conversion module is used to convert analog signals into digital signals; and the data processing unit is used to save and reassemble the array response matrix.
[0045] In this embodiment, a contact-separated TENG-assisted excitation method is used, such as... Figure 3 As shown, after the reference triboelectric layer comes into contact with the surface of the dielectric material under test, equal amounts of opposite charges are generated due to the difference in electron affinity between the materials. When the reference triboelectric layer separates from the test material, a potential difference is formed between them, and an induced signal related to the local interface charge distribution is generated in the arrayed induction electrodes. With periodic contact and separation, electrons flow back and forth in the external circuit, thereby forming a multi-channel triboelectric response signal that can be acquired. This response signal not only reflects the overall charge transfer capability, but also contains information about the local polarization inhomogeneity, interface traps, and low-response regions of the test material.
[0046] 2. Preprocess the multi-channel electrical response signals.
[0047] The acquired multi-channel response signal is denoted as ,in Indicates the first One sensing electrode channel This represents the number of channels. For example... Figure 5 As shown, the original signal undergoes baseline correction, filtering, and normalization to obtain the preprocessed signal:
[0048] in, For filtering operators, For the first Baseline drift term for each channel, This is the channel amplitude normalization coefficient. The characteristic responses of each channel within the same excitation period are recombined into a measurement vector:
[0049] This is the preprocessed array response data, which serves as the input to the interface charge inversion algorithm.
[0050] 3. Establish a positive mapping model between array response and interface charge density distribution.
[0051] The interface of the energy storage dielectric material under test is divided into N charge units, and the interface charge density vector is represented as follows: The positive mapping model between the array response and the interface charge density distribution is expressed as:
[0052] in, The response matrix is determined by the electrode array geometry and dielectric parameters. This is the noise term.
[0053] Response matrix The elements are the response coefficients between the electrodes and charge units in the arrayed inductive electrodes. Specifically, the elements in the response matrix are the response coefficients between the electrodes and charge units. The first electrode pair The response coefficient of a charge unit can be expressed as:
[0054] in, For the first Area of a charge unit For the first The electrode center and the first The horizontal distance between charge units For equivalent medium thickness, The relative permittivity, This is the channel sensitivity coefficient. It is an exponential parameter determined by the form of the potential response or the induced charge response. is the vacuum permittivity.
[0055] 4. Using the array response data as input, the two-dimensional interface charge density distribution map is obtained by solving the interface charge inversion algorithm, with physical constraints applied during the solution process.
[0056] Since the number of electrode channels is typically less than the number of charge units to be inverted, the interface charge inversion problem is an ill-conditioned inverse problem. Therefore, a physically constrained regularized objective function is used to iteratively update the two-dimensional interface charge density distribution map. The physical constraints include smoothness constraints, boundary preservation constraints, non-negativity constraints, and sparsity constraints.
[0057] The objective function is expressed as:
[0058] in, This is the channel weight matrix. For spatial smoothing operators, For spatial gradient operators, , and These represent the weights of the smoothness constraint, boundary preservation constraint, and sparsity constraint, respectively. Non-negativity constraint. The physical rationale for limiting the inversion charge density.
[0059] During the iteration process, the two-dimensional interface charge density distribution map is updated as follows:
[0060] in, Let be the objective function. Step size, For the number of iterations, It is a non-negative projection operator.
[0061] When satisfied
[0062] Alternatively, when the number of iterations reaches a preset limit, the iteration stops and a two-dimensional interface charge distribution map is output. . This is the stopping threshold.
[0063] like Figure 7As shown, compared with the unconstrained inversion results, introducing smoothing constraints can reduce high-frequency noise in the interface charge distribution, but may cause boundary blurring; nonnegative constraints can suppress negative values that do not conform to the physical meaning of interface charge; boundary preservation constraints can reduce noise while preserving the spatial abrupt boundary of the interface charge distribution. The results show that using a combination of multiple physical constraints can balance the stability, physical rationality, and boundary resolution of the inversion results.
[0064] 5. Extract spatial distribution features from the two-dimensional interface charge density distribution map, including average interface charge density, polarization uniformity coefficient, low response region area ratio, and boundary gradient.
[0065] The average interfacial charge density is expressed as:
[0066] The polarization uniformity coefficient is expressed as:
[0067] To prevent constants with a denominator of zero.
[0068] The low response area ratio is expressed as:
[0069] For low response threshold, This is an indicator function. When the condition within the parentheses is true, When the condition inside the parentheses is not true, Therefore, when the first j Charge density of a charge unit Less than the low response threshold At that time, the charge cell is included in the low response region.
[0070] The boundary gradient is expressed as:
[0071] 6. The extracted spatial distribution features are normalized and weighted according to preset weights to establish a parametric evaluation model, yielding polarization capability parameters, polarization uniformity parameters, breakdown weak zone parameters, and local leakage risk parameters. Each performance parameter is expressed as follows:
[0072] in, For the normalized first Spatial distribution characteristics of items The corresponding evaluation weights are determined based on calibrated samples or historical test data. Further weighted calculations are performed on each performance parameter to obtain a comprehensive performance score.
[0073] Calculation of local defect risk index based on spatial distribution characteristics:
[0074] in, The charge decay anomaly factor is determined by the trend of the signal-to-noise ratio change of the interface charge density distribution obtained under different test conditions. , , These are the weighting coefficients.
[0075] Calculate the overall performance score:
[0076] in, to To evaluate the weights, For polarization capability parameters, This is the interface charge stability parameter.
[0077] 7. Based on the score and risk index It can classify the materials to be tested into low-risk, medium-risk, and high-risk levels, and output the corresponding interface charge map, abnormal area location, performance parameter table, and material screening suggestions.
[0078] Among them, when and When it is low risk; when or At that time, it was considered a medium-risk period; when or The risk level is considered high. If the corresponding levels of the two indicators are inconsistent, the higher risk level shall be taken. For example, if the local defect risk index is determined to be medium risk, but the comprehensive performance score is determined to be high risk, or if the local defect risk index is determined to be low risk, but the comprehensive performance score is determined to be medium risk, then the corresponding levels of the two indicators are considered inconsistent, and the final risk level shall be determined according to the one with the higher risk level.
[0079] The above thresholds can be adjusted based on calibration samples or historical test data.
[0080] like Figure 10 As shown, with the advancement of the aging stage and the increase in the number of cycles, the interfacial charge distribution of different energy storage dielectric materials gradually exhibits changes such as local low-response regions, abnormal charge accumulation, and boundary blurring, resulting in a downward trend in the corresponding comprehensive performance score. The rate of score decline varies significantly among different materials, indicating that this invention can identify the degree of performance degradation of materials during aging and cycling, and can be used for material screening, lifetime assessment, and failure risk classification accordingly.
[0081] In summary, the method for interface charge inversion and performance parameter evaluation of energy storage dielectric materials proposed in this invention can comprehensively evaluate local charge accumulation, polarization uniformity, defect-sensitive regions, leakage risk, and breakdown weak regions of energy storage dielectric materials without damaging the material structure. This is achieved through arrayed electrical signal acquisition, interface charge distribution inversion, and spatial characteristic parameter extraction. This provides a non-destructive, visualized, and parameterized testing and analysis method for the screening, structural optimization, aging diagnosis, and service reliability evaluation of energy storage dielectric materials.
[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.
Claims
1. A method for inverting interface charge and evaluating performance parameters of energy storage dielectric materials, characterized in that, The method includes: An arrayed test structure for energy storage dielectric materials, including arrayed sensing electrodes, was constructed. The energy storage dielectric material under test was brought into contact with the arrayed sensing electrodes, and an excitation was applied to induce the energy storage dielectric material under test to generate an interface charge response. Multi-channel electrical response signals at different spatial locations of the energy storage dielectric material under test are acquired by arrayed sensing electrodes, and array response data is obtained by preprocessing the multi-channel electrical response signals. A positive mapping model between array response and interface charge density distribution is established; using array response data as input, a two-dimensional interface charge density distribution map is obtained by solving the interface charge inversion algorithm, with physical constraints applied during the solution process; Spatial distribution features are extracted from the two-dimensional interface charge density distribution map. Based on these features, a parameterized evaluation model for energy storage performance is established, and the performance parameter evaluation results are output.
2. The method according to claim 1, characterized in that, Establishing a positive mapping model between the array response and the interface charge density distribution involves dividing the interface of the energy storage dielectric material under test into N charge units, with the interface charge density vector represented as follows: The positive mapping model between the array response and the interface charge density distribution is expressed as: in, For the response matrix, The noise term is represented by the elements of the response matrix, which are the response coefficients between the electrodes and charge units in the arrayed inductive electrodes.
3. The method according to claim 2, characterized in that, Using array response data as input, the two-dimensional interface charge density distribution map is obtained by solving the interface charge inversion algorithm, including: Based on the forward mapping model and physical constraints, a regularized objective function with physical constraints is constructed. The two-dimensional interface charge density distribution map is updated iteratively through this objective function. When the iteration stops or the number of iterations reaches a preset upper limit, the iteration stops and the two-dimensional interface charge density distribution map is output.
4. The method according to claim 1, characterized in that, Spatial distribution features are extracted from the two-dimensional interface charge density distribution map. These features include the average interface charge density, polarization uniformity coefficient, low response region area ratio, and boundary gradient.
5. The method according to claim 4, characterized in that, Establishing a parameterized evaluation model for energy storage performance based on spatial distribution characteristics includes normalizing the extracted spatial distribution characteristics and weighting them according to preset weights to obtain performance parameters; among which, the performance parameters include polarization capability parameters, polarization uniformity parameters, breakdown weak area parameters, and local leakage risk parameters. Further weighted calculations were performed on each performance parameter to obtain the local defect risk index and the comprehensive performance score.
6. The method according to claim 5, characterized in that, The method also includes classifying the risk level of the energy storage dielectric material under test based on the local defect risk index and comprehensive performance score; Based on the local defect risk index and comprehensive performance score, the energy storage dielectric materials under test are classified into low-risk, medium-risk, or high-risk levels.
7. The method according to claim 1, characterized in that, The arrayed test structure includes a fixed base (1), an arrayed sensing electrode (2), an insulating layer (3), a loading component (5), and a signal output terminal (6). The arrayed sensing electrode (2) is disposed above the fixed base (1), the insulating layer (3) is disposed between the arrayed sensing electrode (2) and the fixed base (1), the loading component (5) is disposed above the arrayed sensing electrode (2), and the signal output terminal (6) is connected to the arrayed sensing electrode (2). The energy storage dielectric material to be tested is fixed between the arrayed sensing electrode (2) and the loading component (5).
8. The method according to claim 7, characterized in that, By applying electric field polarization-release, charge-discharge excitation, contact separation excitation or mechanical disturbance excitation to the energy storage dielectric material under test through the loading component (5), the energy storage dielectric material under test is induced to generate interface charge response.
9. The method according to claim 1, characterized in that, Preprocessing of the multi-channel electrical response signal includes baseline correction, filtering and noise reduction, and amplitude normalization.
10. A system for inverting interface charge and evaluating performance parameters of energy storage dielectric materials for implementing the method of any one of claims 1 to 9, characterized in that, The system includes an arrayed test structure, a signal preprocessing module, an interface charge inversion module, a spatial feature extraction module, and a performance parameter evaluation module; The signal preprocessing module is used to acquire the multi-channel electrical response signal output by the arrayed test structure and preprocess it to obtain the array response data; the interface charge inversion module receives the array response data and generates a two-dimensional interface charge density distribution map. The spatial feature extraction module extracts spatial distribution features from the two-dimensional interface charge density distribution map; The performance parameter evaluation module outputs energy storage performance parameters and the risk level of the energy storage dielectric material under test based on spatial distribution characteristics.