A method for constructing a system-level electromagnetic compatibility data asset

Abstract

The application discloses a kind of construction methods of system-level electromagnetic compatibility data assets, belong to EMC design and test technical field.The method will system EMC feature be decomposed into multivariate function with IC measure, interconnection structure as independent variable, obtain intrinsic data by small system test, and the synergistic, offset and superposition effect between variables are quantified by combination expansion test;Firstly, the system-level EMC data assets including coupling coefficient, combination effect coefficient, compromise coefficient, contribution coefficient and combination effect label are constructed, the electromagnetic characteristics of multi-IC system are quantitatively analyzed, the contribution is traced and the interpretability is analyzed.The application solves the difficulty that system EMC feature cannot be decomposed and multi-factor coupling cannot be quantified in traditional method, and provides complete data support and theoretical basis for complex system design, multi-objective compromise optimization, credible building block simulation and domestic substitution.

Description

Technical Field

[0001] This invention belongs to the field of electromagnetic compatibility (EMC) design and testing technology, specifically relating to a method for constructing system-level electromagnetic compatibility data assets. Background Technology

[0002] With the increasing integration of electronic systems, it has become common for multiple integrated circuits (ICs) to work collaboratively on the same PCB. Electromagnetic interactions occur between different ICs through power networks, signal traces, and spatial coupling, making system-level EMC issues far more complex than those of a single IC.

[0003] Existing technologies typically employ the following methods to address electromagnetic compatibility (EMC) issues in multi-IC systems: First, EMC testing is performed on the entire system as a whole, and rectification is carried out based on the test results. However, this method cannot distinguish the contributions of each integrated circuit and is difficult to quantify the coupling effects between integrated circuits. Second, design is based on the EMC characteristics of a single integrated circuit, but the interaction between integrated circuits is ignored, leading to insufficient design margin or over-design. Third, full-system electromagnetic simulation is used, but the simulation model is complex, computationally intensive, and difficult to calibrate.

[0004] In certain applications with strict limitations on size and weight, such as mobile robots and drones, heavy shielding measures cannot provide electromagnetic protection. When these devices are in complex electromagnetic environments, they often experience functional failures. However, due to the complexity of electromagnetic interactions within the system, designers find it difficult to quickly pinpoint the root cause of the failure and develop targeted protection solutions.

[0005] Another patent filed by the applicant on the same day (a method for constructing IC-level electromagnetic compatibility data assets) solves the problem of constructing EMC data assets for a single integrated circuit, but does not address the system-level electromagnetic compatibility problem when multiple integrated circuits are combined, especially the quantification of coupling effects between ICs. Therefore, there is an urgent need for a method for constructing system-level EMC data assets to quantify the electromagnetic coupling of multi-IC systems and optimize system design. Summary of the Invention

[0006] The purpose of this invention is to provide a method for constructing system-level electromagnetic compatibility data assets, in order to solve the problems of difficulty in quantifying electromagnetic coupling in multi-IC systems and the inability to reuse design experience in the prior art.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for constructing system-level electromagnetic compatibility data assets includes the following:

[0009] Baseline data acquisition: Based on the functional requirements of the target system, determine the combination and interconnection structure of at least two ICs, design and fabricate a micro-system test PCB that enables the system to function properly according to the first rule set, perform EMC testing, and obtain the first test data reflecting the intrinsic electromagnetic characteristics of the system; the micro-system refers to a test system that includes at least two ICs and their necessary peripheral circuits and can realize the basic functions of the system, which is different from the "minimum system" of a single IC; the interconnection structure includes the electrical connection relationship between ICs (such as power supply and signal transmission) and the physical parameters of the interconnection traces (such as length, width, spacing, and coupling method).

[0010] Extended data acquisition: Based on the micro-system, an extended test PCB is designed and fabricated by changing a single design variable according to the second rule set, and EMC testing is performed to obtain second test data reflecting the impact of the design variable on the system's EMC performance; wherein, each extended test changes only one design variable, and all other relevant conditions remain unchanged, including the benchmark test state or the state of the previous extended test.

[0011] Asset Construction: The basic information of the target system, the first test data, the second test data, and the PCB design information, first simulation data and second simulation data used in the benchmark and extended tests are organized into data assets according to a preset data structure, and the data assets are assigned multi-dimensional searchable tags. The tags include at least one or more of the following: system function classification, IC combination type, interconnect structure parameters, EMI performance level, coupling sensitivity and trade-off characteristics.

[0012] Furthermore, the basic information of the target system includes: the model and quantity of ICs, the interconnection relationship between ICs, the system operating frequency, and the system function type.

[0013] Furthermore, the first rule set includes at least one of the following rules:

[0014] Circuit integrity rules are used to ensure the proper configuration of peripheral circuits for the normal operation of the system.

[0015] Physical dimension baseline rules are used to define baseline PCB dimensions;

[0016] The basic rules for stacked structures are used to define the basic stacked structure.

[0017] Port layout baseline rules are used to define the baseline parameters for port routing;

[0018] Decoupling scheme baseline rules are used to define standard decoupling configurations;

[0019] Grounding method reference rules are used to define standard grounding methods;

[0020] Interconnection structure baseline rules are used to define the baseline parameters for interconnection traces between ICs.

[0021] Furthermore, the design variables in the second rule set include at least one of the following types:

[0022] Physical dimension variables, including the planar dimensions of the PCB;

[0023] Layer stack-up variables include the number of PCB layers, stack-up order, and dielectric thickness; filtering measures variables include the presence, type, and parameters of filter circuits.

[0024] Variables of shielding measures include the presence, material, size, and grounding method of the shielding cover;

[0025] Grounding optimization variables include the number, location, and connection method of grounding vias;

[0026] Layout adjustment variables include the relative position of the IC on the PCB and the layout of peripheral components;

[0027] Interconnection structure variables, including the length, width, spacing, and coupling method of traces between ICs;

[0028] Software configuration variables include configurable spread spectrum function, drive strength, slew rate, and operating mode parameters within the IC;

[0029] Environmental variables include ambient temperature, load conditions, and input voltage.

[0030] Furthermore, the method also includes quantitative analysis:

[0031] The second test data obtained from different extended tests are compared with the first test data, and / or the second test data obtained from different extended tests are compared with each other to calculate the quantitative contribution value of each design variable change to the system EMC performance; the quantitative contribution value includes at least one of the following forms:

[0032] Absolute change, expressed in dB, dBμV, dBμV / m, dBμA, dBμA / m as the change in EMC index;

[0033] Relative change, the rate of change of EMC indicators expressed as a percentage; sensitivity coefficient, the change in EMC indicators caused by a unit change in design variables;

[0034] The coupling coefficient characterizes the amount of coupling noise generated between two or more ICs due to electromagnetic interaction, expressed in dB or as a ratio.

[0035] The combined effect coefficient characterizes the relationship between the overall change in the system's EMC performance and the algebraic sum of the individual effects of each variable under changes in a single variable and combinations of variables. It is used to quantify the synergistic effect (overall effect greater than the algebraic sum), offsetting effect (overall effect less than the algebraic sum), or superposition effect (overall effect basically equal to the algebraic sum) among variables.

[0036] The trade-off factor characterizes the degree of trade-off between multiple objectives of the system (including at least two of EMI performance, communication rate, power consumption, and cost);

[0037] The contribution coefficient represents the proportion of a specific IC's characteristics that contribute to the system ports through the interconnect structure. It is used to identify the main contribution sources and propagation paths of system characteristics.

[0038] The coupling coefficient can be calculated by comparing the EMC data difference between IC working together and working alone. Specifically, the coupling coefficient (dB) is calculated as: EMC index value at a certain frequency when working together - EMC index value at the same frequency when working alone, or it can be expressed as a ratio.

[0039] Furthermore, the method also includes simulation calibration:

[0040] A first simulation model corresponding to the test PCB of the microsystem is established. The simulation model is constructed based on the simulation model in the IC-level EMC data asset of each IC. The IC-level EMC data asset refers to the EMC data asset of a single IC that has been pre-constructed.

[0041] Perform EMC simulation to obtain the first simulation data;

[0042] The first simulation data and the first test data are correlated and calibrated to make the deviation between them less than a preset threshold.

[0043] Record the calibration parameters and include the first simulation model and the calibration parameters as part of the data asset.

[0044] Furthermore, the data assets have a hierarchical structure, including at least:

[0045] The system basic information layer stores the basic information of the target system, IC combination types, and interconnection relationships;

[0046] The baseline layer stores the first test data, the corresponding first simulation model, and the PCB design information used for the benchmark test.

[0047] An extension layer stores the second test data under at least one extension dimension, the corresponding second simulation model, and the PCB design information used for the extension test.

[0048] The quantification layer stores the quantified contribution values ​​of the changes in the design variables to the system's EMC performance;

[0049] The tag layer stores the multidimensional searchable tags.

[0050] Furthermore, the multidimensional searchable tags include at least one of the following categories:

[0051] The system function classification labels indicate the system's power supply, communication, control, and hybrid function types;

[0052] IC combination type label indicates the combination of IC types included in the system;

[0053] Interconnection structure parameter labels indicate the length and coupling method of traces between ICs;

[0054] Performance labels indicate the system's EMI strength level or immunity level;

[0055] Coupling sensitivity labels indicate the degree to which a system is sensitive to coupling between ICs;

[0056] The trade-off characteristic label indicates the trade-off relationship between different performance indicators of the system;

[0057] Combination effect labels indicate the synergistic / counteracting / superposition patterns of basic IC combinations under changes in single variables and multivariate combinations, as well as the reference value and predictive value of these patterns for the design of complex systems containing these basic combinations.

[0058] The IC combination type label is used to identify the IC type combination contained in the system, such as "power supply + clock" or "power supply + communication". The trade-off characteristic label is used to describe the trade-off between different performance indicators (such as EMI performance and communication rate). The coupling sensitivity label is used to indicate the sensitivity of the system to changes in interconnect parameters such as IC spacing and trace length. The combination effect label is used to record the effect of the basic IC combination under multivariate changes, providing a predictive basis for complex system design.

[0059] The system-level data assets constructed by this invention, combined with IC-level data assets, enable quantitative analysis of electromagnetic interactions within the system. By utilizing known inter-IC coupling coefficients and sensitivity thresholds of each IC, the propagation path of external interference within the system can be simulated, weak points in the system can be identified, and quantitative protection solutions can be provided for these weak points, such as software configuration adjustments and local filtering measures, thereby improving electromagnetic protection capabilities without significantly increasing the system's size and weight.

[0060] Furthermore, this invention achieves interpretable analysis of the electromagnetic behavior of complex systems by quantitatively constructing and decoupling micro-systems. Specifically:

[0061] Forward quantitative construction: Starting with a single IC, by successively adding ICs with different properties and measuring the changes in the system's EMC characteristics, the electromagnetic contribution of each new IC and its coupling effect with existing ICs are quantified. This process is similar to "electromagnetic titration," where each incremental change can be precisely recorded and quantified.

[0062] Reverse quantitative decoupling: When an EMC anomaly occurs in the system, the coupling coefficients and contribution data of each IC stored in the data assets can be used to reverse-engineer the source of the anomaly. For example, when the system exhibits abnormal radiation at a certain frequency, by comparing the matching degree between that frequency and the intrinsic spectrum of each IC, and analyzing the coupling coefficients between ICs, it is possible to accurately identify which IC is dominant in the radiation at that frequency, and through what path (power network, spatial radiation, signal line) the coupling is generated.

[0063] Co-channel interference identification: When two or more ICs have the same fundamental frequency, the source of interference cannot be distinguished solely from the spectrum. This method analyzes the variation of the coupling coefficient of each IC under different interconnect structure parameters, and combines this with intrinsic data from individual operation to identify the contribution percentage of co-channel interference. For example, by changing interconnect parameters such as IC spacing and trace length, and observing the trend of coupling coefficient changes, the dominant IC and its coupling mechanism can be inferred.

[0064] This invention also provides a system-level EMC data asset, constructed using the above method, wherein the data asset includes at least:

[0065] The system basic information layer stores the basic information of the target system, IC combination types, and interconnection relationships;

[0066] The baseline layer stores the first test data, the corresponding first simulation model, and the PCB design information used for the benchmark test.

[0067] An extension layer stores the second test data under at least one extension dimension, the corresponding second simulation model, and the PCB design information used for the extension test.

[0068] The quantification layer stores the quantified contribution values ​​of the changes in the design variables to the system's EMC performance;

[0069] The tag layer stores multidimensional searchable tags.

[0070] This invention also provides a system for constructing system-level EMC data assets, comprising:

[0071] The rule management module is used to store and manage the first rule set and the second rule set;

[0072] The benchmark module is used to test the system under a microsystem according to the first rule set and obtain the first test data.

[0073] The extended test module is used to test the system after changing a single design variable according to the second rule set and obtain the second test data.

[0074] The quantitative analysis module is used to compare the second test data with the first test data and calculate the quantitative contribution value of the design variable changes to the system EMC performance.

[0075] The asset construction module is used to organize the basic information, test data, simulation data and PCB design information of the target system into data assets and assign them multi-dimensional searchable tags;

[0076] A storage module is used to store the data assets.

[0077] The beneficial effects of this invention are:

[0078] First, this invention solves the problem in the prior art that system-level EMC problems cannot be decomposed and quantified by constructing a micro-system test PCB to obtain intrinsic electromagnetic characteristic data of multi-IC combinations.

[0079] Second, the extended layer data of this invention quantifies the contribution of factors such as physical size, stack-up structure, protection measures, interconnect structure, software configuration, and environmental conditions to the system's EMC performance. In particular, it quantifies the coupling effect between integrated circuits, providing data support for system-level EMC design.

[0080] Third, by constructing a multi-dimensional searchable tag system, this invention enables rapid retrieval, horizontal comparison, and intelligent access to system-level EMC data assets, allowing data obtained from a single test to be reused in multiple system designs.

[0081] Fourth, during the system design phase, data assets from different integrated circuit combinations can be used to predict system-level EMC performance, enabling pre-design assessment and avoiding repeated modifications.

[0082] Fifth, this invention can quantify the trade-offs between different design objectives, such as seeking the optimal balance between EMI performance and communication rate, providing a quantitative basis for multi-objective optimization.

[0083] Sixth, this invention, combined with IC-level data assets, enables quantitative analysis of electromagnetic interactions within a system, identifies weak points in the system, and provides quantitative basis for local protection design, which is of great value in application scenarios where size and weight are limited.

[0084] Seventh, this invention provides a quantitative verification path for domestic system substitution. When there are gaps between the intrinsic data of domestic integrated circuits and imported integrated circuits, the necessary local protection measures can be predicted through the measure sensitivity tags in the data assets, and space can be reserved in the design stage to achieve the feasibility of substitution at minimal cost.

[0085] Eighth, this invention enables interpretable analysis of system-level EMC characteristics. By decoupling forward quantitative construction and reverse quantitative decoupling, it can not only quantify the contribution of each IC and the coupling effect between ICs, but also quickly locate the interference source and identify the coupling path when EMC problems occur, and distinguish the contributions of different ICs with the same baseband frequency, providing unprecedented insights for the EMC design of complex systems. Attached Figure Description

[0086] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0087] Figure 1 This is the overall flowchart of the present invention.

[0088] Figure 2 This is a schematic diagram of the test PCB for the microsystem of this invention (power IC + clock IC combination).

[0089] Figure 3 This is a schematic diagram of the expansion of the interconnect structure variables of the present invention.

[0090] Figure 4 This is a schematic diagram of the quantitative analysis of the coupling effect of the present invention.

[0091] Figure 5 This is a schematic diagram of the system-level data asset structure of this invention.

[0092] Figure 6 This is a diagram illustrating the application of system-level data assets in this invention. Detailed Implementation

[0093] The overall process of this invention includes: S1 establishing a hierarchical standardized test rule set, including a first rule set (rules for small systems) and a second rule set (rules for changing single variables); S2 benchmark layer testing, obtaining the first test data of the system's intrinsic data; S3 simulation modeling and calibration, obtaining the benchmark simulation model and calibration parameters; S4 extension layer construction, with testing and simulation performed in parallel, obtaining the second test data and the second simulation data, and comparing them with the benchmark to calculate the quantitative contribution value; S5 data asset construction and tagging, organizing the above data into hierarchical data assets and assigning multi-dimensional searchable tags.

[0094]

Example 1

[0095] This embodiment uses a combination of a certain type of step-down DC-DC converter (operating frequency 1.2MHz) and a certain type of 50MHz crystal oscillator as an example to illustrate the implementation process of the present invention.

[0096] First, baseline data acquisition was performed. Based on the system functional requirements, the IC combination was determined to be a power IC and a clock IC, with the power IC output supplying power to the clock IC. A microsystem test PCB was designed according to the first rule set. This PCB, measuring 50mm × 50mm, adopted a four-layer structure, containing the two ICs and their necessary peripheral circuits, forming the minimum operating system. Radiated emission testing was performed according to the IEC 61967 standard, with a test frequency range of 30MHz to 1GHz. The test results showed two peak radiations measured at 150MHz and 50MHz, respectively, at 48dBμV / m and 53dBμV / m. This test data was recorded as the first test data. To quantify the coupling effect between the ICs, the radiated emission of the power IC operating alone was tested, with a peak emission of 45dBμV / m at 150MHz; the radiated emission of the clock IC operating alone had a peak emission of 52dBμV / m at 50MHz. The comparison shows that the combined radiation increases by 3dB at 150MHz and by 1dB at 50MHz, indicating a coupling effect.

[0097] Secondly, simulation calibration was performed. A co-simulation model of the microsystem was established based on the simulation models of the power supply IC and clock IC in the IC-level EMC data asset. Electromagnetic simulations were conducted under the same conditions as the test, and the first simulation data was obtained. The first simulation data was compared with the first test data. The initial simulation results showed a large deviation from the measured results, mainly due to the lack of consideration for inter-IC coupling. By adjusting the coupling parameters in the simulation model, the deviation between the simulation results and the measured results was reduced to within 1.5 dB, completing the calibration, and the calibration parameters were recorded.

[0098] Next, extended data acquisition is performed. Following the second set of rules, single design variables are changed sequentially on the basis of the micro-system to conduct extended testing.

[0099] Interconnect structure variable expansion test: The trace length between the power IC output and the clock IC input was changed, with three trace lengths designed: 5mm, 10mm, and 20mm. Test results showed that the longer the trace, the higher the radiation at 150MHz; the 20mm trace was 4dB higher than the 5mm trace. Quantitative calculations showed that for every 5mm increase in trace length, radiation increased by approximately 1.3dB. Changing the trace coupling method, weakly coupled parallel traces (large spacing) and strongly coupled parallel traces (small spacing) were designed. Test results showed that the strongly coupled parallel traces had 3dB lower radiation than the weakly coupled parallel traces. Further changing the trace topology to design differential pair traces, test results showed that the differential pair traces had 3dB lower radiation than the parallel traces.

[0100] Extended Layout Adjustment Test: The relative positions of the two ICs were changed, with three layouts designed with spacing of 5mm, 10mm, and 15mm. Test results showed that the smaller the spacing, the stronger the coupling and the higher the radiation; the 5mm spacing was 5dB higher than the 15mm spacing. Quantitative calculations showed that for every 5mm decrease in spacing, radiation increased by approximately 2.5dB.

[0101] Extended testing of filtering measures: Adding a π-type filter to the power IC output reduced radiation to 40 dBμV / m at 150 MHz, while the 50 MHz radiation from the clock IC remained unaffected. Quantitative calculations showed that this filtering measure reduced coupled radiation by 8 dB.

[0102] Extended shielding test: Adding a local shielding wall between the two ICs resulted in a 42 dBμV / m reduction in radiation at 150 MHz. Quantitative calculations showed that the shielding wall reduced coupled radiation by 6 dB.

[0103] Software configuration extension test: Enabling the spread spectrum function of the power IC, the test results show that the peak radiation at 150MHz decreased from 48dBμV / m to 41dBμV / m. Quantization calculations show that the spread spectrum function reduced radiation by 7dB. Adjusting the drive strength of the clock IC from 100% to 50%, the test results show that the radiation at 50MHz decreased from 53dBμV / m to 48dBμV / m.

[0104] Finally, asset construction is carried out. All the above data is organized into a hierarchical data asset structure.

[0105] The system basic information layer stores basic system information: IC combination type (power supply + clock), interconnection relationship (power supply), system operating frequency (hybrid), and system function classification (hybrid).

[0106] The reference layer stores the first test data (48dBμV / m@150MHz, 53dBμV / m@50MHz), the calibrated first simulation model, and the PCB design information used for the benchmark test (including 50mm×50mm dimensions, four-layer board structure, port layout, etc.).

[0107] The extension layer stores the test data for each extension dimension, the corresponding second simulation data, and the PCB design information used for each extension test.

[0108] Interconnection structure extension: PCB design information for trace lengths of 5mm, 10mm, and 20mm;

[0109] Layout adjustment extension: Layout information for 5mm, 10mm, and 15mm spacing;

[0110] Extended Filtering Measures: Circuit Topology and Parameters of π-Type Filters;

[0111] Shielding measures extended: the structure of local shielding walls;

[0112] Software configuration extensions: configuration parameters for spread spectrum function and drive strength.

[0113] The quantization layer stores the quantified contribution values ​​of changes in each design variable, including:

[0114] Measured values ​​(e.g., 48dBμV / m, 53dBμV / m, 40dBμV / m, etc.);

[0115] The amount of change relative to a reference (e.g., -8dB, -6dB, -7dB, -5dB, etc.);

[0116] Influence coefficients of continuous variables (e.g., 1.3dB / 5mm, 2.5dB / 5mm);

[0117] Coupling coefficient (e.g., 3dB@150MHz);

[0118] The combined effect coefficient (e.g., after applying filtering measures (reducing by 8dB) and shielding measures (reducing by 6dB) simultaneously, the system radiation drops to 35dBμV / m, a total reduction of 13dB, and the combined effect coefficient is 13 / (8+6)=0.93, indicating that the effects are close to superposition, with no obvious synergistic or offsetting effects.

[0119] The tag layer stores multidimensional searchable tags, including:

[0120] System function category tag: Mixed;

[0121] IC combination type label: Power supply + Clock;

[0122] Interconnection structure parameter labels: Trace length 10mm, Coupling method strong coupling;

[0123] Performance label: EMI rating B;

[0124] Coupling sensitivity labels: Spacing sensitive, Trace length sensitive;

[0125] Trade-off characteristic tag: Filtering effect versus cost trade-off;

[0126] Combined effect label: The filtering and shielding effects are approximately independently superimposed (combined effect coefficient 0.93).

[0127] To verify the reverse decoupling capability of this invention, when the system exhibited anomalous radiation at 150MHz, the coupling coefficient and contribution data from the data assets were analyzed. It is known that the power supply IC radiates 45dBμV / m at 150MHz when operating alone, with the clock IC contributing nothing at this frequency; after system integration, the radiation at this frequency is 48dBμV / m, with a coupling coefficient of 3dB. By adjusting the IC spacing from 5mm to 15mm, the 150MHz radiation was observed to decrease from 50dBμV / m to 45dBμV / m, a trend consistent with the coupling sensitivity label "spacing sensitive," thus confirming that the anomaly at this frequency was mainly contributed by the power supply IC and generated through spatial radiation path coupling. This process verifies the reverse decoupling capability of this method for the system's EMC characteristics.

[0128]

Example 2

[0129] This embodiment takes a combination of a certain type of step-down DC-DC converter and a CAN transceiver as an example.

[0130] Perform the baseline data acquisition steps. Design a microsystem test PCB, with the power supply IC powering the CAN transceiver. Perform conducted and radiated emission tests. Test results show that the switching noise of the power supply IC is coupled to the CAN bus through the power network, causing conducted emission peaks in the CAN communication band. When testing the power supply IC alone, the conducted emission is low; when testing the CAN transceiver alone, the conducted emission peak at 5MHz is 65dBμV; when combined, the conducted emission peak at 5MHz is 73dBμV, indicating that power supply noise coupling causes an 8dB increase.

[0131] Perform extended data acquisition steps. Conduct extended interconnect structure variable tests, optimize power traces between the power IC and the CAN transceiver (e.g., shorten traces, increase trace width), and test changes in coupling noise; conduct extended filtering measures tests, add a common-mode choke to the CAN bus, and test the degree of conducted emission reduction; conduct extended software configuration tests, adjust the switching frequency of the power IC to avoid sensitive frequency bands for CAN communication.

[0132] Extended test results show that after optimizing the power supply routing, conducted emissions at 5MHz dropped to 69dBμV (a reduction of 4dB); after adding a common-mode choke, emissions dropped to 56dBμV (a reduction of 17dB); and after adjusting the switching frequency, emissions dropped to 70dBμV (a reduction of 3dB).

[0133] Finally, asset construction is carried out. Multi-dimensional searchable tags are assigned to data assets, including system function classification tags such as communication, IC combination type tags such as power supply + communication, coupling sensitivity tags such as power supply noise sensitivity, and trade-off characteristic tags such as switching frequency and communication quality trade-off.

[0134]

Example 3

[0135] This embodiment uses a flight control system of a certain type of UAV as an example to illustrate the application value of the present invention. This flight control system includes a power IC, a main control IC, a communication IC, and sensor ICs, and has strict weight limitations, making it impossible to use heavy shielding measures.

[0136] Based on the system-level data assets constructed using this invention, combined with IC-level data assets, analysis revealed that communication ICs are most susceptible to failure when interfered with in specific frequency bands, and exhibit strong coupling with power ICs. The IC-level data assets also showed that communication ICs are sensitive to software configuration and can avoid interfering frequency bands by adjusting their operating frequency; power ICs are sensitive to filtering and can be protected by adding a ferrite bead to their output. These protective measures significantly improve the system's adaptability to complex electromagnetic environments without increasing system weight.

[0137]

Example 4

[0138] This embodiment uses two crystal oscillators (clock IC-A and clock IC-B) with an operating frequency of 50MHz as an example to illustrate the co-frequency interference identification capability of the present invention.

[0139] First, the radiated emissions of IC-A and IC-B when operating independently were tested. The results showed that both had a peak radiation of 52 dBμV / m at 50 MHz, and their spectra completely overlapped, making them indistinguishable.

[0140] The two ICs were integrated on the same microsystem test PCB with a spacing of 10mm and weakly coupled parallel traces. Test results showed that the combined ICs had a peak radiation of 58dBμV / m at 50MHz, which was 6dB higher than when operating independently.

[0141] To identify the contribution percentage of the two ICs in this 6dB increment, an interconnect structure variable expansion test was performed:

[0142] Changing the IC spacing: When the spacing is increased to 20mm, the 50MHz radiation drops to 54dBμV / m (a reduction of 4dB).

[0143] Changing the routing coupling method: After changing the parallel routing to differential pair routing, the 50MHz radiation dropped to 55dBμV / m (a reduction of 3dB).

[0144] Data asset analysis reveals that IC-A is more sensitive to spacing changes (its coupling sensitivity label is "spacing sensitive"), while IC-B is more sensitive to routing coupling methods (its coupling sensitivity label is "routing coupling sensitive"). Therefore, it can be inferred that the 4dB reduction caused by spacing changes mainly comes from IC-A, and the 3dB reduction caused by routing changes mainly comes from IC-B. Combining intrinsic data from individual operation, it can be quantitatively calculated that in the combined system, IC-A contributes approximately 3dB of incremental change, and IC-B contributes approximately 3dB of incremental change.

[0145] This process verifies the method's ability to identify co-channel interference. By calculating the contribution coefficients of each IC (in this example, IC-A contributes approximately 3dB and IC-B contributes approximately 3dB), the method achieves quantitative identification of the main contributing sources of system characteristics, solving the problem that traditional spectrum analysis cannot distinguish the sources of co-channel interference.

[0146] Application Examples

[0147] 1. System design and selection scenarios

[0148] Designers can retrieve data assets to compare the system-level EMC performance of different IC combinations and select the optimal combination. For example, for a system that needs to simultaneously meet the requirements of low EMI and high communication speed, the quantitative data of two combinations, "Power Supply A + Communication B" and "Power Supply C + Communication D", can be compared to select the optimal compromise.

[0149] 2. System optimization design scenarios

[0150] Designers can identify the most sensitive coupling components in a system based on coupling sensitivity labels and take targeted measures. For example, if the label indicates that the system is sensitive to IC spacing, sufficient spacing can be prioritized during layout; if it is sensitive to trace length, the trace design can be optimized; if it is sensitive to coupling method, strongly coupled differential pair traces can be prioritized.

[0151] 3. Demonstration scenarios for domestically produced system substitution

[0152] In domestic substitution projects, the feasibility of IC substitution can be quantitatively assessed by comparing the intrinsic data and coupling sensitivity labels of imported and domestic ICs under the same system architecture. For example, in a system using the same power IC, imported and domestic communication ICs are selected respectively. By comparing the radiated emission data of the two at 150MHz (48dBμV / m for the imported IC and 52dBμV / m for the domestic IC), and combining the coupling sensitivity label analysis, if the intrinsic data of the domestic IC is slightly worse but can be achieved at the same level through compensation measures (such as adding filtering or optimizing the layout), then substitution is feasible.

[0153] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for constructing system-level electromagnetic compatibility data assets, characterized in that, Including the following: Baseline data acquisition: Based on the functional requirements of the target system, determine the combination and interconnection structure of at least two ICs, design and fabricate a micro-system test PCB that enables the system to work properly according to the first rule set, perform EMC testing, and obtain the first test data reflecting the intrinsic electromagnetic characteristics of the system. Extended Data Acquisition: Based on the aforementioned micro-system, the system's EMC characteristics are considered as a multivariate function with the individual IC's own measures and the interconnect structure parameters between ICs as independent variables. Following a second set of rules, a single variable or any combination of variables is changed. An extended test PCB is designed and fabricated, and EMC testing is conducted to obtain second test data reflecting the impact of the variable or combination of variables on the system's EMC performance. By changing the measures and interconnect structures of different ICs, the correlation exposure between the overall system EMC characteristics and the characteristics of each IC, the synergistic / counteracting / superposition effects between variables, and the trend relationship of characteristics with multivariate changes are studied. Asset Construction: The basic information of the target system, the first test data, the second test data, and the PCB design information, first simulation data and second simulation data used in the benchmark and extended tests are organized into data assets according to a preset data structure, and the data assets are assigned multi-dimensional searchable tags. The tags include at least one or more of the following: system function classification, IC combination type, interconnect structure parameters, EMI performance level, coupling sensitivity and trade-off characteristics.

2. The method of claim 1, wherein, The basic information of the target system includes: IC model and quantity, interconnection relationship between ICs, system operating frequency, and system function type.

3. The method according to claim 1, characterized in that, The first rule set includes at least one of the following rules: Circuit integrity rules are used to ensure the proper configuration of peripheral circuits for the normal operation of the system. Physical dimension baseline rules are used to define baseline PCB dimensions; The basic rules for stacked structures are used to define the basic stacked structure. Port layout baseline rules are used to define the baseline parameters for port routing; Decoupling scheme baseline rules are used to define standard decoupling configurations; Grounding method reference rules are used to define standard grounding methods; Interconnection structure baseline rules are used to define the baseline parameters for interconnection traces between ICs.

4. The method according to claim 1, characterized in that, The design variables in the second rule set include at least one of the following types: Physical dimension variables, including the planar dimensions of the PCB; Layer stack-up variables include the number of PCB layers, layer stack-up order, and dielectric thickness; Filtering measures variables include the presence, type, and parameters of the filter circuit; Variables of shielding measures include the presence, material, size, and grounding method of the shielding cover; Grounding optimization variables include the number, location, and connection method of grounding vias; Layout adjustment variables include the relative position of the IC on the PCB and the layout of peripheral components; Interconnection structure variables, including the length, width, spacing, and coupling method of traces between ICs; Software configuration variables include configurable spread spectrum function, drive strength, slew rate, and operating mode parameters within the IC; Environmental variables include ambient temperature, load conditions, and input voltage.

5. The method according to claim 1, characterized in that, It also includes quantitative analysis: The second test data obtained from different extended tests are compared with the first test data, and / or the second test data obtained from different extended tests are compared with each other to calculate the quantitative contribution value of each design variable change to the system EMC performance. The quantified contribution value includes at least one of the following forms: Absolute change, expressed in dB, dBμV, dBμV / m, dBμA, dBμA / m as the change in EMC index; Relative change, the rate of change of EMC indicators expressed as a percentage; Sensitivity coefficient, the change in EMC index caused by a unit change in design variables; The coupling coefficient characterizes the amount of coupling noise generated between two or more ICs due to electromagnetic interaction, expressed in dB or as a ratio. The combined effect coefficient characterizes the relationship between the overall change in the system's EMC performance and the algebraic sum of the individual effects of each variable under changes in a single variable and combinations of variables. It is used to quantify the synergistic effect (overall effect greater than the algebraic sum), offsetting effect (overall effect less than the algebraic sum), or superposition effect (overall effect basically equal to the algebraic sum) among variables. The trade-off factor characterizes the degree of trade-off between multiple objectives of the system (including at least two of EMI performance, communication rate, power consumption, and cost); The contribution coefficient represents the proportion of a specific IC's characteristics that contribute to the system ports through the interconnect structure. It is used to identify the main contribution sources and propagation paths of system characteristics.

6. The method according to claim 1, characterized in that, It also includes simulation calibration: A first simulation model corresponding to the test PCB of the micro system is established, and the simulation model is constructed based on the simulation model in the IC-level EMC data assets of each IC; Perform EMC simulation to obtain the first simulation data; The first simulation data and the first test data are correlated and calibrated to make the deviation between them less than a preset threshold. Record the calibration parameters and include the first simulation model and the calibration parameters as part of the data asset; Based on system-level data assets of at least one basic IC combination that have been constructed, simulation modeling is performed on a complex system containing the basic combination. By calling the coupling coefficient, combination effect coefficient and combination effect label of the basic combination, a multivariate simulation model of the complex system is constructed to achieve fast and reliable simulation of the complex system.

7. The method according to claim 1, characterized in that, The data assets have a hierarchical structure and include at least: The system basic information layer stores the basic information of the target system, IC combination types, and interconnection relationships; The baseline layer stores the first test data, the corresponding first simulation model, and the PCB design information used for the benchmark test. An extension layer stores the second test data under at least one extension dimension, the corresponding second simulation model, and the PCB design information used for the extension test. The quantification layer stores the quantified contribution values ​​of the changes in the design variables to the system's EMC performance; The tag layer stores the multidimensional searchable tags.

8. The method according to claim 1, characterized in that, The multidimensional searchable tags include at least one of the following categories: The system function classification labels indicate the system's power supply, communication, control, and hybrid function types; IC combination type label indicates the combination of IC types included in the system; Interconnection structure parameter labels indicate the length and coupling method of traces between ICs; Performance labels indicate the system's EMI strength level or immunity level; Coupling sensitivity labels indicate the degree to which a system is sensitive to coupling between ICs; The trade-off characteristic label indicates the trade-off relationship between different performance indicators of the system, including the multi-objective optimization relationship between EMC performance and power consumption, cost, communication rate, etc. under different IC measures combinations; Combination effect labels indicate the synergistic / counteracting / superposition patterns of basic IC combinations under changes in single variables and multivariate combinations, as well as the reference value and predictive value of these patterns for the design of complex systems containing these basic combinations.

9. A system-level EMC data asset, characterized in that, The data asset is constructed using the method described in any one of claims 1-8, and includes at least: The system basic information layer stores the basic information of the target system, IC combination types, and interconnection relationships; The baseline layer stores the first test data, the corresponding first simulation model, and the PCB design information used for the benchmark test. An extension layer stores the second test data under at least one extension dimension, the corresponding second simulation model, and the PCB design information used for the extension test. The quantification layer stores the quantified contribution values ​​of the changes in the design variables to the system's EMC performance; The tag layer stores multidimensional searchable tags.

10. A system for constructing system-level EMC data assets, characterized in that, include: The rule management module is used to store and manage the first rule set and the second rule set; The benchmark module is used to test the system under a microsystem according to the first rule set and obtain the first test data. The extended test module is used to test the system after changing a single design variable according to the second rule set and obtain the second test data. The quantitative analysis module is used to compare the second test data with the first test data and calculate the quantitative contribution value of the design variable changes to the system EMC performance. The asset construction module is used to organize the basic information, test data, simulation data and PCB design information of the target system into data assets and assign them multi-dimensional searchable tags; A storage module is used to store the data assets.

11. The method according to claim 1, characterized in that, It also includes system design application steps: Based on the system-level EMC data assets and their multivariable function models of at least one built-in basic IC combination, when designing complex systems containing these basic combinations, the following steps are used to achieve rapid system-level EMC design: (a) Retrieval and Combination: Retrieve the trade-off characteristic labels, combination effect labels and contribution coefficients of the basic combination, and construct the initial multivariate function model of the complex system; (b) Feature prediction: Based on the initial model, predict the EMC characteristics and performance trade-offs of complex systems under different combinations of measures; (c) Optimization decision: Based on the prediction results, select the optimal combination of IC measures and interconnect structure to achieve multi-objective optimization of EMC performance, cost, power consumption and other aspects of complex systems; (d) Simulation verification: The prediction results are used as the initial conditions or calibration benchmark for the simulation of complex systems. The simulation verification of complex systems is carried out. If the deviation between the simulation results and the prediction exceeds the preset threshold, the data assets are supplemented and expanded for testing and updates.

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