A method and system for rapid selection of circuit components with optimized matching

Abstract

This invention relates to the field of circuit component selection technology, specifically disclosing a method and system for rapid selection of circuit components through optimized matching. Applied to a circuit component feature database, the method includes: acquiring electrical parameter information corresponding to multiple candidate circuit components; constructing a virtual test model based on the electrical parameter information, and running a virtual circuit based on the virtual test model to generate virtual operation information, wherein the virtual operation information includes multiple virtual dynamic operation parameters corresponding to multiple preset test time points; and obtaining the operating performance information of the virtual circuit based on the virtual operation information. In the evaluation stage, this invention normalizes parameters such as voltage, temperature, and power to generate multi-dimensional correlated change parameters, solving the problem of traditional selection neglecting the performance correlation of components. This allows for accurate evaluation of the comprehensive performance of components in complex scenarios, providing a comprehensive basis for selection.

Description

Technical Field

[0001] This invention relates to the field of circuit component selection technology, and in particular to a method and system for rapid selection of circuit components with optimized matching. Background Technology

[0002] In the field of electronic circuit design, the selection of circuit components is the process of choosing the most suitable components for a specific circuit design based on specific standards and requirements. These standards and requirements cover multiple aspects, including but not limited to electrical performance, physical characteristics, cost, delivery time, and compatibility with other components. Their rationality directly affects the performance, stability, and cost of the circuit system.

[0003] Existing circuit component selection methods have several shortcomings. Traditional methods offer a simplistic and one-sided evaluation of components, typically focusing only on single performance indicators such as voltage stability or power consumption, while neglecting the interrelationships between these indicators and the comprehensive performance requirements of different application scenarios. In practical applications, circuit component performance is often influenced by multiple factors, such as voltage stability and temperature variations, power load and thermal efficiency. Failure to comprehensively consider these factors may result in the selection of components that perform well in some aspects but are unsuitable for the overall requirements, thus affecting the performance and stability of the entire circuit system. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for rapid selection of optimized and matched circuit components, so as to solve the technical problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for rapid selection of circuit components through optimized matching, applied to a circuit component feature database, includes:

[0007] Obtain electrical parameter information for multiple candidate circuit components;

[0008] A virtual test model is constructed based on the electrical parameter information, and a virtual circuit is run based on the virtual test model to generate virtual operation information. The virtual operation information includes multiple virtual dynamic operation parameters corresponding to multiple preset test time points.

[0009] The operating performance information of the virtual circuit is obtained based on the virtual operating information;

[0010] Based on the operational performance information, obtain the multidimensional correlation change parameters of the candidate circuit components at each preset test time point;

[0011] Based on the multidimensional correlation variation parameters, performance evaluation information for assessing the overall performance of circuit components is obtained;

[0012] The matching degree of candidate components is obtained based on the performance evaluation information;

[0013] The matching degree of the candidate components is dynamically adjusted according to a preset matching degree threshold to generate the final recommended matching degree.

[0014] Based on the final recommendation matching degree, all candidate circuit components are sorted to generate a list of recommended components for selection.

[0015] Preferably, the step of constructing a virtual test model based on the electrical parameter information, and running a virtual circuit based on the virtual test model to generate virtual operation information including dynamic operation parameters for multiple preset test time points includes:

[0016] Based on the electrical parameter information, obtain the voltage, current, and temperature parameters;

[0017] A virtual circuit model is constructed based on the voltage, current, and temperature parameters to obtain the virtual circuit topology.

[0018] The initial operating voltage, initial current, and initial temperature are obtained based on the virtual circuit model.

[0019] The load impedance change time interval of the virtual circuit model is obtained based on multiple preset test time points;

[0020] The load impedance change amplitude at each preset test time point is obtained based on the virtual circuit topology.

[0021] A load impedance change curve is established during operation based on the load impedance change magnitude and load impedance change time interval;

[0022] The virtual circuit model is set with dynamic load parameters at multiple preset test time points based on the load impedance change curve. Virtual operating information is obtained based on the dynamic load parameters at multiple preset test time points, wherein the virtual operating information includes instantaneous voltage value, instantaneous current value, and instantaneous temperature value.

[0023] Preferably, the step of obtaining the operating performance information of the virtual circuit based on the virtual operating information includes:

[0024] Extract the instantaneous voltage value at each preset test time point from the dynamic operating parameters;

[0025] The instantaneous voltage difference is obtained based on the maximum and minimum values ​​of the instantaneous voltage.

[0026] Obtain a preset nominal voltage value, and generate a voltage fluctuation value based on the ratio of the instantaneous voltage difference to the nominal voltage value;

[0027] Extract the instantaneous temperature value at each preset test time point from the dynamic operating parameters;

[0028] The temperature rise rate is calculated based on the initial temperature value, the peak temperature value, and the time interval between reaching the peak temperature value.

[0029] The power loss value is calculated based on the instantaneous voltage and current values ​​at each preset test time point;

[0030] The voltage fluctuation value, temperature rise rate value, and power loss value are associated with the corresponding candidate circuit components to generate operating performance information.

[0031] Preferably, the step of obtaining the multidimensional correlation change parameters of the candidate circuit components at each preset test time point based on the operating performance information includes:

[0032] The voltage fluctuation values ​​at each preset test time point are normalized to generate standardized voltage fluctuation parameters;

[0033] The temperature rise rate value at each preset test time point is normalized to generate standardized temperature rise parameters;

[0034] The power loss value at each preset test time point is normalized to generate standardized power parameters;

[0035] Based on the ratio of the standardized voltage fluctuation parameter to the standardized temperature rise parameter, a voltage-temperature change correlation parameter is generated;

[0036] Based on the ratio of the standardized power parameter to the standardized temperature rise parameter, a power-thermal efficiency correlation parameter is generated;

[0037] The voltage-temperature change correlation parameters, power-thermal effect correlation parameters, and load change curve parameters are used as multidimensional correlation change parameters.

[0038] Preferably, the step of obtaining performance evaluation information for assessing the overall performance of the circuit components based on the multidimensional correlation change parameters includes:

[0039] Obtain the type identifier of the circuit application scenario, which includes high voltage stability scenario, high power efficiency scenario and high heat dissipation requirement scenario;

[0040] Based on the type identifier, a first weighting coefficient is assigned to the voltage-temperature change correlation parameter, and a second weighting coefficient is assigned to the power-thermal efficiency correlation parameter;

[0041] A comprehensive performance score is obtained based on the first weighting coefficient, the second weighting coefficient, the voltage-temperature change correlation parameter, and the power-thermal efficiency correlation parameter;

[0042] The overall performance score is compared with a preset performance benchmark value to generate a performance deviation value;

[0043] The overall performance score is adjusted based on the performance deviation value to generate performance evaluation information.

[0044] Preferably, the step of obtaining the matching degree of candidate components based on the performance evaluation information includes:

[0045] Determine whether the matching degree of the candidate component is higher than a preset matching degree threshold;

[0046] If the match degree of the candidate component is higher than the threshold, the match degree of the candidate component is marked as a valid match degree.

[0047] If the value is below the threshold, then extract the failure records related to the current candidate circuit component from the historical failure database.

[0048] The matching degree correction coefficient is obtained based on the failure type and frequency in the failure record;

[0049] The corrected matching degree is obtained by multiplying the matching degree correction coefficient by the matching degree of the candidate component.

[0050] The corrected matching score is used as the final recommended matching score.

[0051] Preferably, the step of sorting all candidate circuit components based on the final recommendation matching degree to generate a list of recommended components includes:

[0052] The candidate circuit components are sorted in descending order based on the final recommended matching degree to generate an initial sorted list;

[0053] Candidate circuit components with the same matching degree are selected from the initial sorted list;

[0054] The cost parameters, delivery cycle parameters, and compatibility parameters of the candidate circuit components are obtained, and the components with the same matching degree are sorted a second time based on the cost parameters, delivery cycle parameters, and compatibility parameters of the candidate circuit components.

[0055] Eliminate candidate circuit components that do not match the preset circuit requirements;

[0056] The selected candidate circuit components are sorted according to the final ranking to generate a list of recommended components.

[0057] This invention also provides a rapid selection system for optimized matching circuit components, comprising:

[0058] The first acquisition module is used to acquire electrical parameter information corresponding to multiple candidate circuit components.

[0059] The second acquisition module is used to construct a virtual test model based on the electrical parameter information, and to run a virtual circuit based on the virtual test model to generate virtual operation information, wherein the virtual operation information includes multiple virtual dynamic operation parameters corresponding to multiple preset test time points;

[0060] The third acquisition module is used to acquire the operating performance information of the virtual circuit based on the virtual operating information;

[0061] The fourth acquisition module is used to acquire the multidimensional correlation change parameters of the candidate circuit components at each preset test time point based on the operating performance information;

[0062] The fifth acquisition module is used to acquire performance evaluation information for evaluating the overall performance of circuit components based on the multidimensional correlation change parameters.

[0063] The sixth acquisition module is used to acquire the matching degree of candidate components based on the performance evaluation information;

[0064] The generation module is used to dynamically correct the matching degree of the candidate components according to a preset matching degree threshold, and generate the final recommended matching degree.

[0065] The sorting module is used to sort all candidate circuit components based on the final recommendation matching degree and generate a list of recommended components for selection.

[0066] Preferably, the second acquisition module includes:

[0067] The first acquisition unit is used to acquire voltage parameters, current parameters, and temperature parameters based on the electrical parameter information.

[0068] The model building unit is used to build a virtual circuit model based on the voltage parameters, current parameters, and temperature parameters, and obtain the virtual circuit topology.

[0069] The second acquisition unit is used to acquire the initial operating voltage, initial current and initial temperature according to the virtual circuit model;

[0070] The third acquisition unit is used to acquire the load impedance change time interval of the virtual circuit model based on multiple preset test time points;

[0071] The fourth acquisition unit is used to acquire the load impedance change amplitude at each preset test time point according to the virtual circuit topology.

[0072] The curve establishment unit is used to establish a load impedance change curve during operation based on the load impedance change amplitude and the load impedance change time interval.

[0073] The fifth acquisition unit is used to set the dynamic load parameters of the virtual circuit model at multiple preset test time points according to the load impedance change curve, and to acquire virtual operation information according to the dynamic load parameters at multiple preset test time points, wherein the virtual operation information includes instantaneous voltage value, instantaneous current value and instantaneous temperature value.

[0074] Preferably, the third acquisition module includes:

[0075] The extraction unit is used to extract the instantaneous voltage value at each preset test time point from the dynamic operating parameters;

[0076] The sixth acquisition unit is used to acquire the instantaneous voltage difference value based on the maximum and minimum values ​​of the instantaneous voltage value;

[0077] The seventh acquisition unit is used to acquire a preset nominal voltage value and generate a voltage fluctuation value based on the ratio of the instantaneous voltage difference to the nominal voltage value.

[0078] The eighth acquisition unit is used to extract the instantaneous temperature value at each preset test time point from the dynamic operating parameters;

[0079] The first calculation unit is used to calculate the temperature rise rate based on the initial temperature value, the peak temperature value, and the time interval between reaching the peak value of the instantaneous temperature.

[0080] The second calculation unit is used to calculate the power loss value based on the instantaneous voltage and current values ​​at each preset test time point;

[0081] The generation unit is used to associate the voltage fluctuation value, temperature rise rate value, and power loss value with the corresponding candidate circuit components to generate operating performance information.

[0082] The beneficial effects of this application are as follows: In the evaluation stage, this invention normalizes parameters such as voltage, temperature, and power to generate multi-dimensional correlation parameters, solving the problem of traditional selection neglecting the performance correlation of components. It can accurately evaluate the comprehensive performance of components in complex scenarios, providing a comprehensive basis for selection. Weighting coefficients are assigned according to the circuit application scenario type, making the evaluation more aligned with actual needs and improving the accuracy and relevance of the evaluation. In terms of matching degree calculation, the matching degree is corrected by combining historical failure databases, avoiding the one-sidedness of selecting based solely on the initial matching degree. This allows the final recommended matching degree to better reflect the true applicability of the components, reducing circuit failure rates and maintenance costs caused by potential component problems. In the sorting and recommendation stage, components with the same matching degree are sorted based on the final recommended matching degree, and then a second sort is performed considering cost, delivery cycle, and compatibility. Components that do not meet the preset conditions are eliminated, generating a clear list of recommended components. This improves selection efficiency and ensures that the selected components meet circuit performance requirements while also taking into account practical factors such as cost and supply, guaranteeing the quality and stability of the circuit design. Attached Figure Description

[0083] Figure 1 This is a schematic diagram of a method flow according to an embodiment of this application.

[0084] Figure 2 This is a schematic diagram of the system structure according to an embodiment of this application.

[0085] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0086] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0087] like Figure 1 As shown, this application provides a method for rapid selection of circuit components through optimized matching, applied to a circuit component feature database, which obtains multiple candidate circuit components based on the circuit component feature database, including:

[0088] S1. Obtain electrical parameter information corresponding to multiple candidate circuit components;

[0089] S2. Construct a virtual test model based on the electrical parameter information, and run a virtual circuit based on the virtual test model to generate virtual operation information, wherein the virtual operation information includes multiple virtual dynamic operation parameters corresponding to multiple preset test time points;

[0090] S3. Obtain the operating performance information of the virtual circuit based on the virtual operating information;

[0091] S4. Obtain the multidimensional correlation change parameters of the candidate circuit components at each preset test time point based on the operational performance information;

[0092] S5. Obtain performance evaluation information for evaluating the overall performance of the circuit components based on the multidimensional correlation change parameters;

[0093] S6. Obtain the matching degree of candidate components based on the performance evaluation information;

[0094] S7. Dynamically adjust the matching degree of the candidate components according to the preset matching degree threshold to generate the final recommended matching degree;

[0095] S8. Sort all candidate circuit components based on the final recommendation matching degree to generate a selection recommendation component list.

[0096] As described in steps S1-S8 above, in the field of electronic circuit design, the selection of circuit components has a crucial impact on the performance and stability of the circuit system. However, traditional selection methods primarily focus on steady-state performance indicators when evaluating component performance, severely neglecting dynamic performance changes during operation. In many practical applications, the operating state of a circuit is not static but dynamically changing. For example, in communication circuits, signal transmission causes continuous changes in voltage and current, which significantly affect the performance of circuit components. Traditional selection methods, failing to consider these dynamic factors, may choose components that perform well in steady-state conditions but poorly in dynamic environments. For instance, a capacitor might meet voltage filtering requirements in steady-state testing, but in a rapidly changing dynamic environment, its response speed cannot keep up with voltage changes, resulting in ineffective filtering and affecting the quality of the communication signal.

[0097] This invention acquires electrical parameter information for multiple candidate circuit components. By comprehensively collecting electrical parameters such as capacitance, equivalent series resistance (ESR), rated voltage, and operating temperature range of candidate capacitors, it avoids the impact of missing key parameters on selection accuracy, ensuring that all electrical factors affecting component performance are considered. Then, a virtual test model is constructed based on the electrical parameter information, and virtual circuit operation is performed to generate virtual operation information. Taking the design of an automotive engine control unit (ECU) circuit as an example, the virtual test model simulates voltage, current, and temperature changes under different driving conditions of the vehicle, and tests candidate power transistors. This can detect potential problems in advance, such as excessively high temperatures exceeding safe ranges under high load and high-temperature ramp conditions, avoiding failures in actual applications and more realistically simulating actual circuit operation. Then, the operating performance information of the virtual circuit is obtained based on the virtual operation information, solving the problem of inaccurate component performance evaluation in traditional selection methods. In solar charging circuit design, by extracting key parameters from virtual operating information, the voltage fluctuation and power loss values ​​of diodes under different light intensities are calculated, accurately evaluating their operating performance at different times. This provides a more comprehensive and accurate performance basis for selection, making the selection more aligned with actual application needs. Then, based on the operating performance information, multi-dimensional correlation parameters of candidate circuit components at preset test time points are obtained, solving the problem of traditional methods that view performance indicators in isolation. In server power supply circuit design, calculating the voltage-temperature change correlation parameters and power-thermal efficiency correlation parameters of inductors can comprehensively consider multiple aspects of performance, such as voltage stability, temperature change, power conversion efficiency, and thermal management, more comprehensively reflecting component performance and making selection more in line with actual complex operating conditions. Subsequently, based on the multi-dimensional correlation parameters generated by S4, performance evaluation information for evaluating the comprehensive performance of circuit components is obtained, solving the problem of traditional selection lacking comprehensive performance evaluation. For example, in medical device circuit design, based on the application scenario requiring high voltage stability, higher weight coefficients are assigned to voltage-temperature change correlation parameters. A comprehensive performance score is calculated and adjusted to achieve accurate evaluation of the overall component performance, ensuring that the selection results meet the performance requirements of specific application scenarios and improving the overall performance and reliability of the circuit system. Subsequently, the matching degree of candidate components is obtained based on the performance evaluation information, solving the problem of inaccurate component matching degree evaluation in traditional selection methods. For instance, in the circuit design of a smart home control system, the preset matching degree threshold is 80%. After evaluating a candidate chip, the initial matching degree is 75%, which is below the threshold. By extracting failure records from a historical failure database, calculating a matching degree correction coefficient, and correcting the matching degree, the accuracy of the matching degree evaluation is improved, ensuring that the recommended components better meet actual needs and reducing the failure rate of the circuit system. Dynamic correction of the matching degree of candidate components based on the preset matching degree threshold generates the final recommended matching degree, solving the problem that traditional selection methods cannot cope with the different component matching degree requirements of different application scenarios.In aerospace circuit design, extremely high component reliability is required, with a preset matching degree threshold set at 95%. A candidate resistor initially assesses a matching degree of 90%. After correction through analysis of historical failure data, a final recommended matching degree of 93% is achieved. Resistors that do not meet the threshold are promptly eliminated, and more reliable components are selected to ensure stable circuit operation in complex environments. In consumer electronics circuit design, the threshold can be appropriately lowered due to cost sensitivity. Lower-cost components are selected by dynamically adjusting the matching degree, improving product market competitiveness. Finally, all candidate circuit components are ranked based on the final recommended matching degree, generating a recommended component list. This solves the problem of traditional selection methods lacking systematicity and comprehensiveness in component ranking and screening. In smartwatch circuit design, facing dozens of candidate components, they are sorted in descending order based on the final recommended matching degree. Components with the same matching degree are then selected, followed by a secondary ranking considering parameters such as cost, delivery time, and compatibility. Incompatible components are eliminated, and the generated recommended component list provides designers with clear selection references, improving selection efficiency and reducing human error.

[0098] In one embodiment, the step of constructing a virtual test model based on the electrical parameter information, running a virtual circuit based on the virtual test model, and generating virtual operation information including dynamic operation parameters at multiple preset test time points includes:

[0099] S201. Obtain voltage parameters, current parameters, and temperature parameters based on the electrical parameter information;

[0100] S202. Construct a virtual circuit model based on the voltage parameters, current parameters, and temperature parameters to obtain the virtual circuit topology.

[0101] S203. Obtain the initial operating voltage, initial current, and initial temperature based on the virtual circuit model;

[0102] S204. Obtain the load impedance change time interval of the virtual circuit model based on multiple preset test time points;

[0103] S205. Obtain the load impedance change amplitude at each preset test time point according to the virtual circuit topology;

[0104] S206. Establish a load impedance change curve during operation based on the load impedance change amplitude and load impedance change time interval;

[0105] S207. Set the dynamic load parameters of the virtual circuit model at multiple preset test time points according to the load impedance change curve, and obtain virtual operation information according to the dynamic load parameters at multiple preset test time points, wherein the virtual operation information includes instantaneous voltage value, instantaneous current value and instantaneous temperature value.

[0106] As described in steps S201-S207 above, this invention obtains voltage, current, and temperature parameters based on electrical parameter information. By accurately acquiring these parameters, reliable data support is provided for constructing a virtual test model and simulating the operation of a real circuit. Then, a virtual circuit model is constructed, and a virtual circuit topology is obtained. Traditional methods struggle to intuitively display the connection relationships and signal transmission paths between components when dealing with complex circuits. For example, in automotive engine control unit (ECU) circuits, traditional methods often fail to clearly present the collaborative working relationships of various parts, affecting the accuracy of component selection. The constructed virtual circuit topology acts like a "map" of the circuit, intuitively showing the connection methods and signal flow of components, facilitating the analysis of interactions between components. Taking the audio amplification circuit of a smart speaker as an example, by constructing a virtual circuit model and topology, impedance mismatch issues between the power amplifier and the speaker can be identified, thereby optimizing circuit design and selection, improving sound quality. By obtaining the initial operating voltage, initial current, and initial temperature based on the virtual circuit model, the initial operating conditions can be clearly defined, allowing simulation of the circuit's startup state and evaluation of component performance during the startup phase. For example, when designing the inverter circuit of an uninterruptible power supply (UPS), by simulating the startup process using initial operating parameters, it was discovered that a certain candidate inverter chip had excessive initial current, causing frequent triggering of the protection circuit and preventing normal startup. Therefore, a more suitable chip was selected to ensure stable UPS startup. The load impedance change time interval of the virtual circuit model was obtained based on multiple preset test time points, overcoming the deficiency of traditional selection methods in simulating the time characteristics of load changes in actual circuits. Precisely setting the load impedance change time interval simulates the dynamic changes of the actual load. The load impedance change amplitude at each preset test time point is obtained based on the virtual circuit topology, solving the problem that traditional selection methods cannot accurately grasp the impact of load impedance change amplitude on component performance. By obtaining the load impedance change amplitude, the degree of actual load change is simulated, and the component's performance under different load change amplitudes is evaluated. A load impedance change curve is established based on the load impedance change amplitude and time interval, solving the problem that traditional selection methods lack a systematic description and analysis of load change patterns. The established load impedance change curve intuitively shows the load change pattern over time, providing a basis for comprehensively evaluating the component's performance under complex load environments. Finally, the dynamic load parameters of the virtual circuit model are set according to the load impedance change curve. This can simulate the real circuit operating environment. When the actual circuit is running, the load is in dynamic change. For example, the voltage and current of the communication circuit will change continuously when the signal is transmitted. The load of the automotive engine control unit (ECU) circuit is also different under different driving conditions. Setting dynamic load parameters and simulating this change according to the load impedance change curve can make the virtual test model closer to the real situation. The setting of dynamic load parameters is closely related to the acquisition of virtual operating information. Its purpose is to comprehensively obtain the key data of the components under dynamic operating conditions.During virtual circuit operation, based on the set dynamic load parameters, instantaneous voltage, current, and temperature values ​​are collected at preset test time points to obtain virtual operating information. This solves the problem of traditional selection methods failing to realistically simulate dynamic load conditions during testing by acquiring virtual operating information based on dynamic load parameters at multiple preset test time points. By setting dynamic load parameters and acquiring virtual operating information, the dynamic load environment of the actual circuit is realistically simulated, obtaining key data of components under dynamic operating conditions. Dynamic load parameters are set using load impedance change curves to simulate load changes during takeoff and landing, obtaining virtual operating information.

[0107] In one embodiment, the step of obtaining the operating performance information of the virtual circuit based on the virtual operating information includes:

[0108] S301. Extract the instantaneous voltage value at each preset test time point from the dynamic operating parameters;

[0109] S302. Obtain the instantaneous voltage difference value based on the maximum and minimum values ​​of the instantaneous voltage;

[0110] S303. Obtain a preset nominal voltage value, and generate a voltage fluctuation value based on the ratio of the instantaneous voltage difference to the nominal voltage value;

[0111] S304. Extract the instantaneous temperature value at each preset test time point from the dynamic operating parameters;

[0112] S305. Calculate the temperature rise rate based on the initial temperature value, peak temperature value, and time interval between reaching the peak value of the instantaneous temperature.

[0113] S306. Calculate the power loss value based on the instantaneous voltage and current values ​​at each preset test time point;

[0114] S307. Associate the voltage fluctuation value, temperature rise rate value, and power loss value with the corresponding candidate circuit components to generate operating performance information.

[0115] As described in steps S301-S307 above, this invention extracts the instantaneous voltage value at each preset test time point from dynamic operating parameters. By pre-setting a monitoring mechanism in the virtual test model, the instantaneous voltage value is accurately extracted from a large amount of operating data according to the test time points determined based on the actual operating characteristics of the circuit. The instantaneous voltage value is extracted, and the instantaneous voltage difference is obtained based on the maximum and minimum values. By organizing the extracted instantaneous voltage values, the maximum and minimum values ​​are found and subtracted to obtain the instantaneous difference value, which intuitively reflects the voltage fluctuation range. Next, a preset nominal voltage value is obtained, and the voltage fluctuation value is generated based on the ratio of the instantaneous voltage difference value to the nominal voltage value. For example, in the design of control circuits for industrial automated production lines, traditional selection lacks a unified standard to assess the impact of voltage fluctuations on component performance, making it difficult to determine whether voltage fluctuations will affect equipment operation. First, the preset nominal voltage value of the circuit is determined, and then the voltage fluctuation value is obtained by dividing the instantaneous voltage difference value by the nominal voltage value. By calculating voltage fluctuation values ​​and comparing these values ​​with those of different candidate power modules, the module with the smallest voltage fluctuation value is selected. This ensures that the server can operate under stable voltage, providing a unified standard for evaluating the adaptability of components under the same voltage fluctuation environment. This facilitates the selection of highly adaptable components. Instantaneous temperature values ​​are extracted from dynamic operating parameters at each preset test time point. The temperature rise rate is calculated based on the initial temperature value, peak temperature value, and time interval between reaching the peak value. Relevant parameters are then determined from the extracted instantaneous temperature values, and the temperature rise rate is calculated using a specific formula. Power loss values ​​are calculated based on the instantaneous voltage and current values ​​at each preset test time point. At each preset test time point, the extracted instantaneous voltage value is multiplied by the instantaneous current value at the same moment to obtain the instantaneous power, and then the power loss value is calculated through statistical analysis. Finally, the voltage fluctuation value, temperature rise rate value, and power loss value are associated with the corresponding candidate circuit components to generate operational performance information. The calculated temperature rise rate value and power loss value are linked to the corresponding candidate circuit components through component identifiers and integrated into an operational performance information table. It provides a comprehensive and systematic evaluation basis for selection, improves the overall performance and reliability of the circuit, and reduces failures caused by component performance mismatch.

[0116] In one embodiment, the step of obtaining the multidimensional correlation change parameters of the candidate circuit component at each preset test time point based on the operating performance information includes:

[0117] S401. Normalize the voltage fluctuation value at each preset test time point to generate standardized voltage fluctuation parameters.

[0118] S402. Normalize the temperature rise rate value at each preset test time point to generate standardized temperature rise parameters;

[0119] S403. Normalize the power loss value at each preset test time point to generate standardized power parameters;

[0120] S404. Generate voltage-temperature change correlation parameters based on the ratio of the standardized voltage fluctuation parameters to the standardized temperature rise parameters;

[0121] S405. Generate power-thermal efficiency correlation parameters based on the ratio of the standardized power parameters to the standardized temperature rise parameters;

[0122] S406. The voltage-temperature change correlation parameters, power-thermal effect correlation parameters, and load change curve parameters are used as multidimensional correlation change parameters.

[0123] As described in steps S401-S406 above, this invention normalizes the voltage fluctuation value at each preset test time point to generate standardized voltage fluctuation parameters. In the traditional circuit component selection process, due to the vastly different operating voltage ranges and test environments of different circuits, it is difficult to compare the voltage fluctuation values ​​of different components under the same standard. Taking mobile phone motherboards and industrial control boards as examples, mobile phone motherboards have low operating voltages, while industrial control boards have high operating voltages and complex environments. Their voltage fluctuation values ​​lack a unified reference standard, making it extremely difficult to judge the voltage stability of components. S401, by determining the maximum and minimum values ​​of the voltage fluctuation values ​​of all candidate components, uses a normalization formula to map the voltage fluctuation value at each preset test time point to the [0,1] interval, achieving a fair comparison of the voltage fluctuation performance of different components. The temperature rise rate value at each preset test time point is normalized to generate standardized temperature rise parameters. Different components have different heating characteristics and heat dissipation environments, making it difficult to directly compare their temperature rise rates. By statistically analyzing the temperature rise rate values ​​of all candidate components, their maximum and minimum values ​​are determined. Then, a normalization formula is used to transform the temperature rise rate values ​​into the [0,1] interval, providing a unified standard for evaluating the heat dissipation of different components. The power loss values ​​at each preset test time point are normalized to generate standardized power parameters. Traditional selection methods cannot measure component power loss under a unified standard when facing circuits with different power levels and operating modes. By statistically analyzing the power loss values ​​of all candidate components, determining the maximum and minimum values, and using a normalization formula to transform the power loss values ​​into standardized parameters, the power loss of different components can be intuitively compared on the same scale. Then, based on the ratio of the standardized voltage fluctuation parameter to the standardized temperature rise parameter, a voltage-temperature change correlation parameter is generated. Traditional selection methods often consider the impact of voltage fluctuation and temperature change on component performance in isolation, ignoring the intrinsic relationship between the two. Dividing the standardized voltage fluctuation parameter and the standardized temperature rise parameter yields the voltage-temperature change correlation parameter, comprehensively considering the relationship between the two. Based on the ratio of the standardized power parameter to the standardized temperature rise parameter, a power-thermal efficiency correlation parameter is generated. Traditional component selection methods struggle to accurately determine the relationship between power loss and thermal effects during component evaluation. In power conversion module design, power loss is converted into heat, and traditional methods cannot effectively analyze the correlation between the two. This may lead to the selection of components with low thermal efficiency, increasing the heat dissipation burden and affecting the performance and lifespan of the power module. By dividing the standardized power parameter by the standardized temperature rise parameter, a power-thermal efficiency correlation parameter is generated, quantifying the relationship between the two. By comparing with other candidate components, selecting components with smaller power-thermal efficiency correlation parameters can improve power supply thermal efficiency, reduce heat dissipation costs, and ensure stable server operation. Finally, the voltage-temperature change correlation parameter, the power-thermal efficiency correlation parameter, and the load change curve parameter are used as multi-dimensional correlation change parameters.The previously generated correlation parameters are integrated with the load change curve parameters to form multidimensional correlation change parameters, which comprehensively reflect the overall performance of the component in terms of electrical, thermal performance and load change.

[0124] In one embodiment, the step of obtaining performance evaluation information for assessing the overall performance of circuit components based on the multidimensional correlation change parameters includes:

[0125] S501. Obtain the type identifier of the circuit application scenario, wherein the type identifier includes high voltage stability scenario, high power efficiency scenario and high heat dissipation requirement scenario.

[0126] S502. Assign a first weighting coefficient to the voltage-temperature change correlation parameter according to the type identifier, and assign a second weighting coefficient to the power-thermal efficiency correlation parameter;

[0127] S503. Obtain a comprehensive performance score based on the first weighting coefficient, the second weighting coefficient, the voltage-temperature change correlation parameter, and the power-thermal effect correlation parameter;

[0128] S504. Compare the comprehensive performance score with the preset performance benchmark value to generate a performance deviation value;

[0129] S505. Adjust the comprehensive performance score according to the performance deviation value to generate performance evaluation information.

[0130] As described in steps S501-S505 above, this invention addresses the problem of traditional evaluation methods neglecting the differentiated performance requirements of components in different scenarios by acquiring the type identifier of the circuit application scenario, including high voltage stability scenarios, high power efficiency scenarios, and high heat dissipation requirement scenarios. In actual circuit design, different application scenarios have drastically different focuses on component performance. Before selection, a detailed analysis of the circuit application scenario is conducted, and the scenario type is determined and its identifier is obtained through communication with designers, review of materials, or analysis of the actual usage environment. This provides direction for subsequent evaluation work, ensuring that the selection process closely revolves around actual needs and avoiding the selection of unsuitable components due to misjudgment of the scenario. Based on the scenario type identifier obtained in S501, a first weighting coefficient and a second weighting coefficient are assigned to the voltage-temperature change correlation parameter and the power-thermal efficiency correlation parameter, respectively, according to the identifier. Traditional evaluation methods use fixed weights for these parameters, which cannot reflect the differences in the importance of each parameter under different scenarios. In high voltage stability scenarios, the voltage-temperature change correlation parameter has a greater impact on component performance; while in high power efficiency scenarios, the power-thermal efficiency correlation parameter is more important. Weighting rules are established based on scenario types, such as pre-setting weight coefficient tables for different scenarios and selecting corresponding weight coefficients according to the type identifier. Taking the circuit of a high-power laser cutting equipment as an example, it belongs to the high-power efficiency scenario. According to the rules, a first weight coefficient of 0.3 is assigned to the voltage-temperature change correlation parameter, and a second weight coefficient of 0.7 is assigned to the power-thermal efficiency correlation parameter. This weighting allocation highlights key performance indicators, making the evaluation results more in line with the actual scenario requirements, and providing a more scientific standard for selecting suitable components. A comprehensive performance score is obtained based on the first weight coefficient, the second weight coefficient, the voltage-temperature change correlation parameter, and the power-thermal efficiency correlation parameter, solving the problem that traditional methods cannot comprehensively reflect the overall performance of components with a single parameter. The voltage-temperature change correlation parameter and the power-thermal efficiency correlation parameter describe the component performance from different perspectives, but considering them alone cannot yield the overall performance of the component in a specific scenario. The comprehensive performance score is obtained by multiplying the voltage-temperature change correlation parameter by the first weight coefficient, multiplying the power-thermal efficiency correlation parameter by the second weight coefficient, and then adding the two products. For example, when designing a power supply circuit for a data center server, a candidate component has a voltage-temperature variation correlation parameter of 0.5 and a first weighting coefficient of 0.4, a power-thermal efficiency correlation parameter of 0.6 and a second weighting coefficient of 0.6. The calculated comprehensive performance score S = 0.4 × 0.5 + 0.6 × 0.6 = 0.56. This score comprehensively and objectively reflects the component's overall performance in this scenario, helping to select better options from numerous candidate components and improve the overall circuit performance. By comparing the comprehensive performance score with a preset performance benchmark value, a performance deviation value is generated, solving the problem of traditional evaluations lacking comparison with benchmark values ​​and making it difficult to determine whether a component meets actual requirements.Different application scenarios have different expected standards for component performance. Relying solely on the overall performance score cannot intuitively determine whether a component meets the standards. This paper addresses the problem of inaccurate results caused by traditional evaluations that directly use the overall performance score without considering deviations from the benchmark. The overall performance score may contain errors due to various factors, and the performance deviation reflects the relationship between these errors and actual requirements. The overall performance score is adjusted based on the sign and magnitude of the performance deviation. A positive deviation increases the score, while a negative deviation decreases it. The adjustment range is determined based on the actual situation, and the adjusted score becomes the performance evaluation information. For example, in designing circuits for scenarios with high heat dissipation requirements, a candidate component has an overall performance score of 0.65, a preset benchmark of 0.7, and a deviation of -0.05. Considering the stringent heat dissipation requirements of the scenario, the score is reduced by 0.1, resulting in a final performance evaluation of 0.55. This information more accurately reflects the actual performance of the component, helping to make more reasonable selection decisions and improve circuit design quality and reliability.

[0131] In one embodiment, the step of obtaining the matching degree of candidate components based on the performance evaluation information includes:

[0132] S601. Determine whether the matching degree of the candidate component is higher than the preset matching degree threshold;

[0133] If the match degree of the candidate component is higher than the threshold, the match degree of the candidate component is marked as a valid match degree.

[0134] If the value is below the threshold, then extract the failure records related to the current candidate circuit component from the historical failure database.

[0135] S602. Obtain the matching degree correction coefficient based on the failure type and frequency in the failure record;

[0136] S603. Multiply the matching degree correction coefficient by the candidate component matching degree to obtain the corrected matching degree;

[0137] S604. The corrected matching degree is taken as the final recommended matching degree.

[0138] As described in steps S601-S604 above, this invention determines whether the matching degree of candidate components is higher than a preset matching degree threshold. In the traditional circuit component selection process, the applicability of components is often determined solely by subjective judgment or a single performance indicator. This can easily lead to the incorrect selection of unsuitable components or the missed opportunity to select components that may be suitable after improvement. By setting a clear preset matching degree threshold, an objective standard is provided for the initial screening of components. The determination of this threshold is based on past experience, the specific requirements of the circuit design, and a large amount of experimental data. When the matching degree of a candidate component is higher than the threshold, it is marked as a valid matching degree, indicating that the component has a high degree of matching with the circuit design requirements in the initial evaluation and can proceed to the subsequent more detailed evaluation stage. If it is lower than the threshold, relevant failure records are extracted from the historical failure database. For example, when designing the power circuit of a smartwatch, the preset matching degree threshold is 70%. If the matching degree of a candidate power chip is 75%, its matching degree is marked as valid. However, if the matching degree of another chip is 65%, which is lower than the threshold, it is necessary to search the database for failure records of that chip or similar chips. For example, it may be found that the chip has low charging efficiency in low-temperature environments. This step quickly filters out components that initially meet the requirements, while laying the foundation for in-depth analysis of components with low matching scores. Based on the failure records extracted by S601, a matching score correction coefficient is obtained according to the failure type and frequency in the failure records, solving the problem of traditional selection neglecting the historical failure information of components. Traditional methods often only focus on the current performance indicators when evaluating components, ignoring problems that have occurred during the component's past use. Different failure types and frequencies have different impacts on the reliability of components in actual applications. If these factors are not considered, components that are prone to failure in actual use may be selected. A detailed analysis of failure records is conducted, failure types are classified, such as short circuits, overheating, signal interference, etc., and the frequency of each failure type is statistically analyzed. Based on the severity and frequency of failure types, corresponding rules are formulated to determine the matching score correction coefficient. The matching score correction coefficient is multiplied by the matching score of the candidate components to obtain the corrected matching score, solving the problem that the initial matching score cannot accurately reflect the actual applicability of the component. The initial matching score of candidate components does not fully consider the impact of the component's historical failures on its reliability in actual circuits. If the initial matching score is used directly for selection, the actual performance of the component may be overestimated or underestimated. By combining the two through multiplication, the resulting corrected matching degree more accurately reflects the true degree of matching of the component after considering historical failure factors. Finally, the corrected matching degree is used as the final recommended matching degree, solving the problem of lacking a unified and accurate reference standard in the selection process. Throughout the entire candidate component selection process, the previous preliminary matching degree and correction process are all aimed at obtaining an indicator that can accurately reflect the degree of fit between the component and the circuit design requirements.Without a clear final matching degree as a recommendation basis, the selection process may become chaotic, hindering the making of scientific and rational decisions. Determining the revised matching degree as the final recommended matching degree provides a unified and accurate reference standard for circuit component selection. Designers can use this final matching degree to compare and filter among multiple candidate components, prioritizing those with high matching degrees.

[0139] In one embodiment, the step of sorting all candidate circuit components based on the final recommendation matching degree to generate a list of recommended components includes:

[0140] S701. Sort the candidate circuit components in descending order according to the final recommended matching degree to generate an initial sorted list;

[0141] S702. Select candidate circuit components with the same matching degree from the initial sorting list;

[0142] S703. Obtain the cost parameters, delivery cycle parameters, and compatibility parameters of the candidate circuit components, and perform a secondary sorting of the components with the same matching degree based on the cost parameters, delivery cycle parameters, and compatibility parameters of the candidate circuit components.

[0143] S704. Eliminate candidate circuit components that do not match the preset circuit requirements.

[0144] S705. Generate a list of recommended components based on the final sorting results of the screened candidate circuit components.

[0145] As described in steps S701-S705 above, this invention sorts candidate circuit components in descending order based on the final recommended matching degree, generating an initial sorted list, thus solving the problem of unclear component priorities in traditional selection. In previous selection processes, faced with numerous candidate components, the lack of an effective sorting method made it difficult for designers to quickly determine which components better met their needs, resulting in low selection efficiency and insufficient accuracy. This invention collects the final recommended matching degree data of all candidate circuit components and uses a sorting algorithm to arrange the components from high to low matching degree, forming a clear initial sorted list. Candidate circuit components with the same matching degree are then selected, solving the problem of difficulty in distinguishing the superiority or inferiority of components with the same matching degree in the initial sorting. Traditional selection methods often fail to further refine the evaluation when encountering components with the same matching degree, easily leading to random selection and potentially missing more advantageous components. By traversing the initial sorted list and comparing the matching degrees of adjacent components, components with the same matching degree are extracted to form a dedicated sublist. This method obtains cost, lead time, and compatibility parameters for candidate circuit components and then re-ranks components with the same degree of matching based on these parameters. This solves the problem that relying solely on matching degree cannot comprehensively evaluate the quality of components. Traditional selection often ignores key factors such as cost, lead time, and compatibility, leading to the selection of components that may be too expensive, have delayed delivery, or be incompatible with other circuit parts. The method obtains cost, lead time, and compatibility parameters, assigns weights to each parameter, calculates a comprehensive score, and then ranks the components in descending order based on the score. For example, among two chips with the same degree of matching, one chip has a lower cost but a longer lead time, while the other chip has a slightly higher cost but a shorter lead time and better compatibility. Through the comprehensive evaluation in step S703, the chip with better overall performance in terms of cost, lead time, and compatibility can be selected, reducing circuit design costs, ensuring on-time delivery, improving overall circuit compatibility, and eliminating candidate circuit components that do not match the preset circuit requirements. This solves the problem of potentially selecting components that do not meet the basic requirements of the circuit in previous selection methods. During the preceding sorting process, some components, while showing a high degree of matching, may not meet key pre-defined conditions, such as operating voltage range or power requirements. Failure to eliminate these components would impact the quality and schedule of the circuit design. By clearly defining the pre-defined circuit requirements and examining each ranked candidate component, those that do not meet the criteria are removed from the list. Finally, a recommended component list is generated based on the final ranking of the selected candidate circuit components, resolving the issue of unclear presentation of the selection results. After the preceding screening and sorting, a clear list is needed to display the final recommendations; otherwise, designers will struggle to make choices amidst a wealth of component information. The remaining candidate components after screening are organized into a list containing information such as component name, matching degree, and overall score, according to the final ranking.After all the screening and sorting is completed in the smart speaker circuit design, the generated selection recommendation component list clearly presents the key information of each component. Designers can easily select the appropriate components according to the list order, improving selection efficiency and accuracy.

[0146] like Figure 2 As shown, the present invention also provides a rapid selection system for optimized matching circuit components, comprising:

[0147] The first acquisition module 1 is used to acquire electrical parameter information corresponding to multiple candidate circuit components;

[0148] The second acquisition module 2 is used to construct a virtual test model based on the electrical parameter information, and to run a virtual circuit based on the virtual test model to generate virtual operation information, wherein the virtual operation information includes multiple virtual dynamic operation parameters corresponding to multiple preset test time points;

[0149] The third acquisition module 3 is used to acquire the operating performance information of the virtual circuit based on the virtual operating information;

[0150] The fourth acquisition module 4 is used to acquire the multidimensional correlation change parameters of the candidate circuit components at each preset test time point based on the operating performance information;

[0151] The fifth acquisition module 5 is used to acquire performance evaluation information for evaluating the overall performance of circuit components based on the multidimensional correlation change parameters;

[0152] The sixth acquisition module 6 is used to acquire the matching degree of candidate components based on the performance evaluation information;

[0153] The generation module 7 is used to dynamically correct the matching degree of the candidate components according to a preset matching degree threshold, and generate the final recommended matching degree.

[0154] The sorting module 8 is used to sort all candidate circuit components based on the final recommendation matching degree and generate a list of recommended components for selection.

[0155] In one embodiment, the second acquisition module 2 includes:

[0156] The first acquisition unit is used to acquire voltage parameters, current parameters, and temperature parameters based on the electrical parameter information.

[0157] The model building unit is used to build a virtual circuit model based on the voltage parameters, current parameters, and temperature parameters, and obtain the virtual circuit topology.

[0158] The second acquisition unit is used to acquire the initial operating voltage, initial current and initial temperature according to the virtual circuit model;

[0159] The third acquisition unit is used to acquire the load impedance change time interval of the virtual circuit model based on multiple preset test time points;

[0160] The fourth acquisition unit is used to acquire the load impedance change amplitude at each preset test time point according to the virtual circuit topology.

[0161] The curve establishment unit is used to establish a load impedance change curve during operation based on the load impedance change amplitude and the load impedance change time interval.

[0162] The fifth acquisition unit is used to set the dynamic load parameters of the virtual circuit model at multiple preset test time points according to the load impedance change curve, and to acquire virtual operation information according to the dynamic load parameters at multiple preset test time points, wherein the virtual operation information includes instantaneous voltage value, instantaneous current value and instantaneous temperature value.

[0163] In one embodiment, the third acquisition module 3 includes:

[0164] The extraction unit is used to extract the instantaneous voltage value at each preset test time point from the dynamic operating parameters;

[0165] The sixth acquisition unit is used to acquire the instantaneous voltage difference value based on the maximum and minimum values ​​of the instantaneous voltage value;

[0166] The seventh acquisition unit is used to acquire a preset nominal voltage value and generate a voltage fluctuation value based on the ratio of the instantaneous voltage difference to the nominal voltage value.

[0167] The eighth acquisition unit is used to extract the instantaneous temperature value at each preset test time point from the dynamic operating parameters;

[0168] The first calculation unit is used to calculate the temperature rise rate based on the initial temperature value, the peak temperature value, and the time interval between reaching the peak value of the instantaneous temperature.

[0169] The second calculation unit is used to calculate the power loss value based on the instantaneous voltage and current values ​​at each preset test time point;

[0170] The generation unit is used to associate the voltage fluctuation value, temperature rise rate value, and power loss value with the corresponding candidate circuit components to generate operating performance information.

[0171] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in this application and in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0172] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0173] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent results or equivalent process transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for rapid selection of circuit components through optimized matching, applied to a circuit component feature database, characterized in that, include: Obtain electrical parameter information for multiple candidate circuit components; A virtual test model is constructed based on the electrical parameter information, and a virtual circuit is run based on the virtual test model to generate virtual operation information. The virtual operation information includes multiple virtual dynamic operation parameters corresponding to multiple preset test time points. The operating performance information of the virtual circuit is obtained based on the virtual operating information; Based on the operational performance information, obtain the multidimensional correlation change parameters of the candidate circuit components at each preset test time point; Based on the multidimensional correlation variation parameters, performance evaluation information for assessing the overall performance of circuit components is obtained; The matching degree of candidate components is obtained based on the performance evaluation information; The matching degree of the candidate components is dynamically adjusted according to a preset matching degree threshold to generate the final recommended matching degree. Based on the final recommendation matching degree, all candidate circuit components are sorted to generate a list of recommended components for selection.

2. The method for rapid selection of optimized matching circuit components according to claim 1, characterized in that, The step of constructing a virtual test model based on the electrical parameter information, running a virtual circuit based on the virtual test model, and generating virtual operation information including dynamic operation parameters at multiple preset test time points includes: Based on the electrical parameter information, obtain the voltage, current, and temperature parameters; A virtual circuit model is constructed based on the voltage, current, and temperature parameters to obtain the virtual circuit topology. The initial operating voltage, initial current, and initial temperature are obtained based on the virtual circuit model. The load impedance change time interval of the virtual circuit model is obtained based on multiple preset test time points; The load impedance change amplitude at each preset test time point is obtained based on the virtual circuit topology. A load impedance change curve is established during operation based on the load impedance change magnitude and load impedance change time interval; The virtual circuit model is set with dynamic load parameters at multiple preset test time points based on the load impedance change curve. Virtual operating information is obtained based on the dynamic load parameters at multiple preset test time points, wherein the virtual operating information includes instantaneous voltage value, instantaneous current value, and instantaneous temperature value.

3. The method for rapid selection of optimized matching circuit components according to claim 1, characterized in that, The step of obtaining the operating performance information of the virtual circuit based on the virtual operating information includes: Extract the instantaneous voltage value at each preset test time point from the dynamic operating parameters; The instantaneous voltage difference is obtained based on the maximum and minimum values ​​of the instantaneous voltage. Obtain a preset nominal voltage value, and generate a voltage fluctuation value based on the ratio of the instantaneous voltage difference to the nominal voltage value; Extract the instantaneous temperature value at each preset test time point from the dynamic operating parameters; The temperature rise rate is calculated based on the initial temperature value, the peak temperature value, and the time interval between reaching the peak temperature value. The power loss value is calculated based on the instantaneous voltage and current values ​​at each preset test time point; The voltage fluctuation value, temperature rise rate value, and power loss value are associated with the corresponding candidate circuit components to generate operating performance information.

4. The method for rapid selection of optimized matching circuit components according to claim 1, characterized in that, The step of obtaining the multidimensional correlation change parameters of the candidate circuit components at each preset test time point based on the operating performance information includes: The voltage fluctuation values ​​at each preset test time point are normalized to generate standardized voltage fluctuation parameters; The temperature rise rate value at each preset test time point is normalized to generate standardized temperature rise parameters; The power loss value at each preset test time point is normalized to generate standardized power parameters; Based on the ratio of the standardized voltage fluctuation parameter to the standardized temperature rise parameter, a voltage-temperature change correlation parameter is generated; Based on the ratio of the standardized power parameter to the standardized temperature rise parameter, a power-thermal efficiency correlation parameter is generated; The voltage-temperature change correlation parameters, power-thermal effect correlation parameters, and load change curve parameters are used as multidimensional correlation change parameters.

5. The method for rapid selection of optimized matching circuit components according to claim 4, characterized in that, The step of obtaining performance evaluation information for assessing the overall performance of circuit components based on the multidimensional correlation change parameters includes: Obtain the type identifier of the circuit application scenario, which includes high voltage stability scenario, high power efficiency scenario and high heat dissipation requirement scenario; Based on the type identifier, a first weighting coefficient is assigned to the voltage-temperature change correlation parameter, and a second weighting coefficient is assigned to the power-thermal efficiency correlation parameter; A comprehensive performance score is obtained based on the first weighting coefficient, the second weighting coefficient, the voltage-temperature change correlation parameter, and the power-thermal efficiency correlation parameter; The overall performance score is compared with a preset performance benchmark value to generate a performance deviation value; The overall performance score is adjusted based on the performance deviation value to generate performance evaluation information.

6. The method for rapid selection of optimized matching circuit components according to claim 1, characterized in that, The step of obtaining the matching degree of candidate components based on the performance evaluation information includes: Determine whether the matching degree of the candidate component is higher than a preset matching degree threshold; If the match degree of the candidate component is higher than the threshold, the match degree of the candidate component is marked as a valid match degree. If the value is below the threshold, then extract the failure records related to the current candidate circuit component from the historical failure database. The matching degree correction coefficient is obtained based on the failure type and frequency in the failure record; The corrected matching degree is obtained by multiplying the matching degree correction coefficient by the matching degree of the candidate component. The corrected matching score is used as the final recommended matching score.

7. The method for rapid selection of optimized matching circuit components according to claim 1, characterized in that, The step of sorting all candidate circuit components based on the final recommendation matching degree to generate a list of recommended components includes: The candidate circuit components are sorted in descending order based on the final recommended matching degree to generate an initial sorted list; Candidate circuit components with the same matching degree are selected from the initial sorted list; The cost parameters, delivery cycle parameters, and compatibility parameters of the candidate circuit components are obtained, and the components with the same matching degree are sorted a second time based on the cost parameters, delivery cycle parameters, and compatibility parameters of the candidate circuit components. Eliminate candidate circuit components that do not match the preset circuit requirements; The selected candidate circuit components are sorted according to the final ranking to generate a list of recommended components.

8. A rapid selection system for optimized matching circuit components, characterized in that, include: The first acquisition module is used to acquire electrical parameter information corresponding to multiple candidate circuit components; The second acquisition module is used to construct a virtual test model based on the electrical parameter information, and to run a virtual circuit based on the virtual test model to generate virtual operation information, wherein the virtual operation information includes multiple virtual dynamic operation parameters corresponding to multiple preset test time points; The third acquisition module is used to acquire the operating performance information of the virtual circuit based on the virtual operating information; The fourth acquisition module is used to acquire the multidimensional correlation change parameters of the candidate circuit components at each preset test time point based on the operating performance information; The fifth acquisition module is used to acquire performance evaluation information for evaluating the overall performance of circuit components based on the multidimensional correlation change parameters. The sixth acquisition module is used to acquire the matching degree of candidate components based on the performance evaluation information; The generation module is used to dynamically correct the matching degree of the candidate components according to a preset matching degree threshold, and generate the final recommended matching degree. The sorting module is used to sort all candidate circuit components based on the final recommendation matching degree and generate a list of recommended components for selection.

9. The circuit component rapid selection system for optimized matching according to claim 8, characterized in that, The second acquisition module includes: The first acquisition unit is used to acquire voltage parameters, current parameters, and temperature parameters based on the electrical parameter information. The model building unit is used to build a virtual circuit model based on the voltage parameters, current parameters, and temperature parameters, and obtain the virtual circuit topology. The second acquisition unit is used to acquire the initial operating voltage, initial current and initial temperature according to the virtual circuit model; The third acquisition unit is used to acquire the load impedance change time interval of the virtual circuit model based on multiple preset test time points; The fourth acquisition unit is used to acquire the load impedance change amplitude at each preset test time point according to the virtual circuit topology. The curve establishment unit is used to establish a load impedance change curve during operation based on the load impedance change amplitude and the load impedance change time interval. The fifth acquisition unit is used to set the dynamic load parameters of the virtual circuit model at multiple preset test time points according to the load impedance change curve, and to acquire virtual operation information according to the dynamic load parameters at multiple preset test time points, wherein the virtual operation information includes instantaneous voltage value, instantaneous current value and instantaneous temperature value.

10. The circuit component rapid selection system for optimized matching according to claim 8, characterized in that, The third acquisition module includes: The extraction unit is used to extract the instantaneous voltage value at each preset test time point from the dynamic operating parameters; The sixth acquisition unit is used to acquire the instantaneous voltage difference value based on the maximum and minimum values ​​of the instantaneous voltage value; The seventh acquisition unit is used to acquire a preset nominal voltage value and generate a voltage fluctuation value based on the ratio of the instantaneous voltage difference to the nominal voltage value. The eighth acquisition unit is used to extract the instantaneous temperature value at each preset test time point from the dynamic operating parameters; The first calculation unit is used to calculate the temperature rise rate based on the initial temperature value, the peak temperature value, and the time interval between reaching the peak value of the instantaneous temperature. The second calculation unit is used to calculate the power loss value based on the instantaneous voltage and current values ​​at each preset test time point; The generation unit is used to associate the voltage fluctuation value, temperature rise rate value, and power loss value with the corresponding candidate circuit components to generate operating performance information.

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