Cold-pressed terminal quality evaluation and prediction method and system

Abstract

The invention discloses a cold-pressed terminal quality evaluation and prediction method and system, and belongs to the technical field of electrical connector quality detection. According to the method, limitation of traditional single physical quantity detection is abandoned, a full-dimensional failure model including mechanical failure, electrical failure, electrochemical failure and creep failure is constructed, and an electricity-heat-force multi-physical field coupling simulation technology is introduced, so that accurate prediction of the potential failure mode of the cold-pressed terminal is realized. The core lies in that a quantitative index system from microscopic measurement and control to macroscopic performance is established, and multi-source heterogeneous test data is converted into a unified comprehensive quality index through a hierarchical weighted scoring algorithm. According to the method, the accelerated aging profile test and the digital twin comparison are integrated, the risk can be identified in the product design stage or the production early stage, the evaluation efficiency and reliability are greatly improved, and a scientific basis is provided for quality grading, life prediction and process optimization of the cold-pressed terminal.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of electrical connector quality detection and reliability evaluation, and particularly relates to a systematic and predictive quality evaluation and life prediction method for cold-press terminals in low-voltage electrical systems. BACKGROUND

[0002] Cold-press terminals are components that achieve the connection of wires and electrical equipment through mechanical pressure connection, and are widely used in the fields of automobiles, household appliances, industrial control, new energy, etc. The reliability of the connection is directly related to the safety and stability of the entire electrical system. Currently, the quality evaluation of cold-press terminals mainly relies on a series of standardized single performance tests.

[0003] The existing evaluation methods generally have the following limitations:

[0004] Discretization and one-sidedness: The current method usually takes pull-out force test, contact resistance test, salt spray test, temperature rise test, etc. as independent pass / fail judgment items. This "island type" test cannot reveal the strong coupling relationship between mechanical performance, electrical performance and environmental tolerance. For example, a terminal that passes the standard pull-out force test may cause local overheating under high current due to micro air gaps in the pressure connection area, and eventually fail prematurely due to creep and oxidation leading to a decrease in contact pressure. There is a lack of correlation analysis between the test results, making it difficult to form a comprehensive understanding of the overall reliability of the terminal.

[0005] Post-test mode: The traditional quality evaluation is a typical "production-test-determination" post-test mode. Quality problems are often discovered at the finished product stage or even after customer application, at which time the cost of design or process changes is high and the cycle is long. There is a lack of effective means for risk prediction and performance pre-evaluation in the early stages of product design, mold development, process parameter setting, etc.

[0006] Ignoring the micro quality root cause: The reliability of the cold-press terminal connection ultimately depends on the microstructure quality of the pressure connection area, such as the degree of plastic deformation fusion of the wire and the sleeve metal, the size and distribution of internal air gaps, the deformation uniformity of the wire filaments, etc. The existing standards lack mandatory requirements for quantitative and standardized detection and control of these key micro features. Defects in the microstructure are the cause of long-term aging failure, but traditional macroscopic tests cannot effectively trace back.

[0007] Lack of comprehensive quantitative evaluation system: In the face of terminals produced by different suppliers and different process parameters, it is difficult to intuitively and scientifically rank the advantages and disadvantages based on multiple independent test reports. The industry urgently needs a single quantitative index that can comprehensively evaluate the key attributes and reflect the inherent reliability level of the terminal, which can be used for quality grading, supply chain management and continuous improvement.

[0008] Long test period and high cost: Natural aging or conventional accelerated life tests required for evaluating long-term reliability often take months or even years, which cannot quickly respond to product development pace and market changes.

[0009] Therefore, it is of great significance to develop an innovative quality evaluation method that can start from failure mechanism, integrate simulation prediction, micro-analysis, macro-test and comprehensive evaluation throughout the whole product life cycle, and improve the technical level, product quality and reliability design capability of the cold press terminal industry. SUMMARY

[0010] The purpose of the present application is to overcome the shortcomings of the prior art and provide a systematic, mechanism-driven and predictable quality evaluation and prediction method for cold press terminals. The method aims to: establish a full-dimensional failure physical model covering all potential failure modes of cold press terminals. Define a series of key quality indicators directly related to failure mechanisms and quantifiable from micro to macro. Introduce the electric-thermal-mechanical multi-physical field coupling simulation technology to predict the performance short board and risk point of the terminal in the design stage. Design an efficient accelerated aging profile test, and form a "virtual-physical" verification closed loop with the simulation results. Develop a grading weighted scoring algorithm to integrate all test and simulation data and output an intuitive comprehensive quality index for objective evaluation and grading. Finally, realize the paradigm shift of quality control from "post-test" to "early prediction" and from "single item compliance" to "system optimization".

[0011] To achieve the above purpose, the present application proposes the following technical solutions:

[0012] A cold press terminal quality evaluation and prediction method, characterized in that it comprises the following steps:

[0013] S1: Construct a full-dimensional failure model of cold press terminals, which includes at least mechanical failure sub-model, electrical failure sub-model, electrochemical failure sub-model and creep failure sub-model;

[0014] S2: According to the full-dimensional failure model, define and obtain a group of corresponding core quantitative evaluation indicators, which include at least microstructure indicators, electrical performance indicators, mechanical performance indicators and environmental tolerance indicators;

[0015] S3: Establish an electric-thermal-mechanical multi-physical field coupling simulation digital model of the cold press terminal, input material properties, geometric dimensions, crimping process parameters and load working conditions, and simulate the stress distribution, temperature rise characteristics and current density distribution under the expected working conditions;

[0016] S4: Design and perform a set of accelerated aging profile tests, which contain at least three or more combined stresses of temperature cycling, humidity storage, current load cycling and vibration stress;

[0017] S5: Measure the indicators described in step S2 on the sample after the test in step S4, and compare the measured data with the simulation prediction results in step S3 using digital twins to verify and correct the simulation model.

[0018] S6: Based on the revised simulation model and measured data, a graded weighted scoring algorithm is used to calculate the score of each evaluation indicator, and finally a comprehensive quality index is obtained.

[0019] S7: Based on the comprehensive quality index and the preset threshold, the quality level of the cold-pressed terminal is determined, and its service life under different working conditions is predicted based on simulation and test data.

[0020] The present invention further provides that the microstructure indicators include: the material compression rate and filling rate of the terminal crimping area, as well as the internal air gap rate and the uniformity of the deformation of the single wire obtained by metallographic analysis, wherein the filling rate is defined as the ratio of the cross-sectional area of ​​the metal wire to the cross-sectional area of ​​the inner contour of the terminal sleeve after crimping.

[0021] The present invention further includes a milliohm-level initial contact resistance and its stability coefficient after a short-term high-current impact, wherein the stability coefficient is the ratio of the resistance value after the impact to the initial value; and the steady-state temperature rise value under rated current.

[0022] The present invention further provides that the mechanical performance indicators include: axial pull-out force, cyclic bending fatigue cycles, and contact normal force measured by a micro-force tester, wherein the contact normal force needs to be measured directly or indirectly at the contact interface under simulated assembly conditions.

[0023] The present invention further provides that the environmental tolerance indicators include: the corrosion weight gain rate and contact resistance change rate after salt spray test, and the insulation resistance decrease rate after temperature-humidity-bias current composite test.

[0024] The present invention further specifies that, in step S3, the electro-thermal-mechanical multiphysics coupling simulation specifically involves: taking the current load as input, calculating the temperature field caused by Joule heating, then coupling the thermal stress caused by the temperature field with the mechanical stress, analyzing the stress concentration and plastic deformation region of the terminal structure, and simultaneously feeding the temperature field back to the material conductivity for iterative calculation until convergence.

[0025] In a further embodiment of the present invention, in step S4, the accelerated aging profile test is designed using a time-temperature compression model based on failure physics, compressing the actual working conditions of several years into hundreds of hours. The combined stress is applied sequentially in a asynchronous, variable amplitude manner to simulate a real complex environment.

[0026] The present invention further specifies that, in step S6, the specific process of the graded weighted scoring algorithm is as follows: First, a threshold of four levels—excellent, good, average, and poor—is set for each indicator; then, the indicator level is determined based on the measured or simulated values ​​and a base score is assigned; next, the indicator is weighted according to its weight coefficient in the full-dimensional failure model; finally, all weighted scores are summed to obtain a comprehensive quality index between 0 and 100.

[0027] The present invention further includes step S8: establishing a mapping relationship database of process parameters, quality indicators, and comprehensive quality index of the cold-pressed terminal, and training a model through machine learning methods to back-optimize key process parameters such as crimping mold design, crimping height, and pressure.

[0028] The present invention also proposes a cold-pressed terminal quality assessment system for implementing the method, characterized in that it includes at least: a coupled simulation calculation module, a test data acquisition module, a digital twin comparison analysis module, and a comprehensive index calculation and prediction module.

[0029] Compared with existing technologies, this invention has the following significant advantages: Starting from failure physics, it constructs an evaluation framework covering all failure modes, avoiding the one-sidedness of traditional methods. Through multiphysics simulation, performance and risks can be predicted during mold development and sample prototyping stages, guiding design optimization and reducing development costs and cycles. All evaluation indicators point to specific failure mechanisms, providing a clear scientific direction for quality improvement and achieving "quality control moving forward to the root cause." The Comprehensive Quality Index (CQI) normalizes complex technical data into an intuitive score, facilitating horizontal comparison and hierarchical management between different products, batches, and suppliers. Accelerated profiling tests based on failure physics, compared to traditional single-item sequential tests or natural aging, can more efficiently induce failure and shorten the verification cycle. The "simulation-experiment-correction-prediction" process allows each evaluation to accumulate data and correct the model, forming a continuously self-improving knowledge system that can be used for reverse optimization of process parameters (such as optimal pressing height and pressure). Attached image description:

[0030] Figure 1 This is a flowchart illustrating an embodiment of the present invention. Detailed Implementation

[0031] The embodiments of this application will be described in detail below, providing a clear and complete description of the technical solutions within this application. Obviously, the described embodiments are merely a portion of the embodiments of this application, and not all of them. The components of this application described and shown herein can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0032] like Figure 1 As shown, this invention provides a method for evaluating and predicting the quality of cold-pressed terminals, with the following specific steps:

[0033] Step S1: Construct a full-dimensional failure model for cold-pressed terminals

[0034] A systematic analysis of all possible failure modes of cold-pressed terminals throughout their entire lifespan is conducted, and these modes are summarized into four interrelated sub-models:

[0035] Mechanical failure sub-model: covers metal fatigue fracture, fretting wear, plastic deformation and mechanical damage to terminal structures caused by vibration, bending, insertion and removal, external tension.

[0036] Electrical failure sub-model: covers overheating, melting, electrical erosion (arc) and deterioration of insulation performance caused by excessive or unstable contact resistance.

[0037] Electrochemical failure sub-model: covers galvanic corrosion, crevice corrosion, stress corrosion cracking, and oxide film thickening that occur in environments such as humidity, salt spray, and polluted gases.

[0038] Creep failure sub-model: This model covers the slow plastic deformation of metallic materials under long-term temperature and stress (especially residual pressure stress and contact spring stress), which leads to continuous relaxation of contact pressure.

[0039] The core of this model lies in elucidating the coupling effects between the various sub-models. For example, electrochemical corrosion products increase contact resistance (electrochemical coupling), leading to increased Joule heating (electrothermal coupling), which in turn accelerates creep and further oxidation (thermomechanical-chemical coupling), ultimately resulting in connection failure. This model forms the theoretical basis for defining evaluation indicators and designing experiments.

[0040] Step S2: Define and obtain core quantitative evaluation indicators

[0041] Based on the full-dimensional failure model, four categories of measurable and quantifiable indicators are defined:

[0042] Microstructure index group: reflects the intrinsic quality of the crimping process.

[0043] Material compressibility (CR): CR = (A_wire - A_crimp) / A_wire × 100%, where A_wire is the nominal cross-sectional area of ​​the wire, and A_crimp is the actual minimum cross-sectional area of ​​the wire metal after crimping, obtained by anatomical measurement or micro-CT scan.

[0044] Fill Ratio (FR): FR = A_wire / A_sleeve × 100%, where A_sleeve is the inner contour cross-sectional area of ​​the crimped terminal sleeve. FR is a key indicator for evaluating the tightness of the sleeve material in wrapping the wire, and the ideal value is close to 1.

[0045] Internal air gap ratio (Vg): The percentage of the total air gap area to the field of view of the pressing area is calculated by image processing software after metallographic sectioning and polishing, and image capture under scanning electron microscope or high-magnification optical microscope.

[0046] Uniformity of deformation of individual filaments in a conductor (UD): This quantifies the consistency of deformation of each filament after crimping. It is assessed by calculating the standard deviation of the bending angle of each filament or by identifying the number of filaments with severe warping or breakage.

[0047] Electrical performance indicators: reflect the immediate and short-term electrical characteristics of the connection.

[0048] Initial contact resistance (Rc0): In the micro-ohm range, measured at low current (e.g., 1A) using a DC four-terminal method (Kelvin connection) to eliminate the influence of thermal effects.

[0049] Contact resistance stability coefficient (k_s): Apply N (e.g., 5) short-duration rated current surges (e.g., lasting 1 minute) to the terminals, and record the contact resistance Rc_i after each surge and cooling to room temperature. Calculate k_s = σ / Rc_avg, where σ is the standard deviation of Rc_i and Rc_avg is the average value. The smaller the k_s, the higher the stability.

[0050] Rated current steady-state temperature rise (ΔT): In a test chamber at a specified ambient temperature (e.g., 25°C), the rated current is applied to the terminals, and the temperature of the hottest spot is monitored using a thermocouple or infrared thermal imager until thermal equilibrium is reached (temperature difference <2°C within 1 hour). The difference between the temperature rise and the ambient temperature is then calculated.

[0051] Mechanical performance indicators: reflect the mechanical strength and holding power of the connection.

[0052] Axial pull-out force (F_pull): Apply axial tensile force at a constant rate on a tensile testing machine according to standard methods until the connection fails (the wire is pulled out or breaks), and record the peak force.

[0053] Normal contact pressure (F_normal): The normal pressure at the contact interface is obtained by using a miniature force sensor or by measuring the deformation of the contact spring in a simulated interlocking state, combined with inverse calculations using a material mechanics model. This pressure is fundamental to maintaining low contact resistance.

[0054] Cyclic bending fatigue life (N_f): The terminal with the wire is fixed, and a periodic bending stress is applied to the wire at a certain distance from the crimping area. The number of cycles until the terminal or wire cracks or the resistance increases sharply is recorded.

[0055] Environmental tolerance index group: reflects long-term reliability.

[0056] Performance change rate after salt spray test: After a neutral salt spray test for a specified time (e.g., 96 hours), measure the change rate of contact resistance ΔRc_salt=(Rc_after-Rc0) / Rc0×100%, and observe and record the corrosion morphology level.

[0057] Performance change rate after temperature-humidity-bias test: Under dual 85 (85℃, 85%RH) conditions, the rated current is applied to the terminals simultaneously (THB test) for a specified period of time (e.g., 500 hours), and the rate of decrease in insulation resistance and the rate of change in contact resistance are measured.

[0058] Step S3: Establish a digital model for coupled electro-thermal-mechanical multiphysics simulation.

[0059] Geometric modeling and mesh generation: Based on the accurate CAD models of the terminals and mating connectors, necessary simplifications are made (such as ignoring chamfers that do not affect the results), and the models are imported into the finite element analysis software. Mesh refinement is performed on key areas (crimp-fit ​​areas, contact points, stress concentration areas).

[0060] Material property definition: The precise properties of input terminal materials (such as brass and copper) and conductor materials (such as copper alloys), including: electrical conductivity, thermal conductivity, specific heat capacity as a function of temperature, and nonlinear elastoplastic stress-strain curves.

[0061] Boundary conditions and load settings:

[0062] Electric field: A rated current or current density is applied to one end of the terminal, and the other end is set to ground.

[0063] Thermal field: Set the environmental convective heat transfer coefficient and consider radiative heat dissipation. Apply the Joule heat calculated from the electric field as a heat source to the model.

[0064] Structural field: Apply necessary constraints (fix a part of the terminal), and apply the residual stress field generated by the simulated crimping process (which can be imported through simplification or sub-model), as well as the assembly preload in the mating state.

[0065] Coupled solution: Sequential or direct coupled analysis is performed. A typical process is as follows: Current generates Joule heating → Temperature rise leads to changes in material properties and thermal expansion → Thermal expansion couples with mechanical stress to generate thermal stress and deformation → Deformation may change the contact area and pressure, thus influencing the current density and heat generation distribution. Iterative calculations continue until convergence.

[0066] Results Analysis and Risk Identification: Post-processing yielded the following key cloud maps and data:

[0067] Current density distribution cloud map: Identify areas of current congestion (hot spots).

[0068] Temperature distribution cloud map: predicts the highest temperature and location during steady-state operation.

[0069] Stress / strain distribution cloud map (Mises stress): Identifies potential plastic deformation zones and fatigue crack initiation points.

[0070] Contact pressure distribution cloud map: assesses the pressure uniformity of the contact interface.

[0071] Step S4: Design and execute accelerated aging profile tests

[0072] Based on a comprehensive failure model and practical application environment, a composite stress accelerated test profile is designed, rather than a single stress test. Example profile (cycle 24 hours):

[0073] Phase 1 (High Temperature and High Humidity Storage): 4 hours, temperature 85℃, relative humidity 85%, no power supply.

[0074] Phase 2 (Temperature Shock): Five cycles were performed, with rapid transitions from -40°C (30 minutes) to +125°C (30 minutes) to examine thermal expansion mismatch.

[0075] Phase 3 (Vibration Stress): Apply broadband random vibration at room temperature for 2 hours, with a frequency range of 10-2000Hz. The RMS acceleration level is set according to the application scenario (e.g., automotive applications).

[0076] Phase 4 (Current Load Cycle): 8 hours, with the rated current (4 hours) and zero current (4 hours) alternately cycled to simulate the actual working conditions.

[0077] This profile combines thermal, humidity, mechanical, and electrical stresses in an asynchronous and sequential manner, which can more effectively stimulate a variety of potential failure mechanisms. The total test duration can be compressed and set according to the target equivalent life (e.g., 10 years) using an accelerated model (e.g., Coffin-Manson, Arrhenius).

[0078] Step S5: Digital Twin Comparison and Model Correction

[0079] Data acquisition and alignment: Measure the performance indicators of the sample (such as contact resistance and temperature rise after different test cycles) during or after accelerated testing.

[0080] Simulation-experiment comparison: The temperature rise-time curve and resistance degradation trajectory obtained from the experiment are superimposed and compared with the corresponding curves predicted by the simulation in step S3.

[0081] Model Correction: If the deviation exceeds the acceptable range (e.g., >15%), analyze the cause and adjust the parameters with higher uncertainty in the simulation model in reverse, such as contact resistivity, interfacial thermal resistance, convective heat transfer coefficient, and material degradation function after aging. Through iterative correction, the behavior of the digital model is made to approximate the real behavior of the physical entity infinitely, thereby establishing a high-fidelity "digital twin".

[0082] Step S6: Graded weighted scoring algorithm and comprehensive quality index calculation

[0083] Indicator grading and base score assignment: Four threshold levels are set for each evaluation indicator: "Excellent (A)," "Good (B)," "Satisfactory (C)," and "Unsatisfactory (D)." These thresholds are determined based on industry benchmarks, historical data, theoretical extreme values, and standard requirements. For example:

[0084] Pull-off force F_pull: ≥150% of the standard value is A (90 points), ≥120% of the standard value is B (80 points), ≥ the standard value is C (70 points), < the standard value is D (50 points).

[0085] Fill rate (FR): ≥95% is A, ≥90% is B, ≥85% is C, <85% is D.

[0086] The change in electrical resistance ΔRc_salt after salt spray: ≤10% is A, ≤25% is B, ≤50% is C, and >50% is D.

[0087] Weight coefficient determination: Using the analytic hierarchy process (AHP), based on the specific application scenario (such as the different environmental severity of an automotive engine compartment and an indoor electrical distribution box), the relative importance of each indicator to the final reliability in the full-dimensional failure model is determined. Pairwise comparisons are performed to construct a judgment matrix, and the weights Wi of each indicator (satisfying ΣWi=1) are calculated and verified. For harsh environments, the weight of the environmental tolerance indicator can be appropriately increased.

[0088] Overall Quality Index Calculation:

[0089] CQI = Σ(S_i*W_i)

[0090] Where S_i is the base score of index i based on its measurement / simulation value (the score corresponding to A / B / C / D). CQI is a value between 0 and 100.

[0091] Level determination:

[0092] CQI≥90: Excellent. The product has extremely high reliability and is suitable for the most demanding applications.

[0093] 80≤CQI<90: Excellent grade. The product has high reliability and meets the requirements of most applications.

[0094] 70≤CQI<80: Pass grade. The product meets the basic requirements and can be used in general scenarios.

[0095] CQI < 70: Non-compliant. The product poses a clear risk and requires improvement.

[0096] Step S7: Quality Assessment and Lifespan Prediction

[0097] Quality assessment: Based on the calculated CQI and its level, a clear quality conclusion is given for batch products or different design schemes.

[0098] Service life prediction: Using a modified high-fidelity digital twin model, detailed load and environmental spectra of the target application scenario (such as automotive-grade temperature cycling spectra and current load spectra) are input for long-term virtual simulation. When key parameters in the simulation model (such as contact resistance and contact pressure) degrade to the failure threshold, the corresponding virtual time is the predicted service life of that terminal.

[0099] If certain terms are used in the specification and claims to refer to specific components, those skilled in the art will understand that hardware manufacturers may use different names to refer to the same component. This specification and claims do not distinguish components based on differences in name, but rather on differences in function. The term "comprising" as used throughout the specification and claims is an open-ended term and should be interpreted as "comprising but not limited to." "Approximately" means that within an acceptable margin of error, those skilled in the art can solve the technical problem and substantially achieve the technical effect within a certain margin of error.

[0100] It should be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a product or system comprising a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a product or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the product or system that includes that element.

[0101] The foregoing description illustrates and describes several preferred embodiments of the present invention. However, as previously stated, it should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the inventive concept by means of the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A method for evaluating and predicting the quality of cold-pressed terminals, characterized in that, Includes the following steps: S1: Construct a full-dimensional failure model for cold-pressed terminals, which includes at least a mechanical failure sub-model, an electrical failure sub-model, an electrochemical failure sub-model, and a creep failure sub-model. S2: Based on the full-dimensional failure model, define and obtain a set of corresponding core quantitative evaluation indicators, which include at least microstructure indicators, electrical performance indicators, mechanical performance indicators and environmental tolerance indicators. S3: Establish a digital simulation model of the electro-thermal-mechanical multiphysics coupling of the cold-pressed terminal, input material properties, geometric dimensions, crimping process parameters and load conditions, and simulate and calculate its stress distribution, temperature rise characteristics and current density distribution under the expected working conditions. S4: Design and execute an accelerated aging profile test, the profile of which includes at least three or more combinations of stresses from temperature cycling, humidity storage, current load cycling and vibration stress. S5: Measure the indicators described in step S2 on the sample after the test in step S4, and compare the measured data with the simulation prediction results in step S3 using digital twins to verify and correct the simulation model. S6: Based on the revised simulation model and measured data, a graded weighted scoring algorithm is used to calculate the score of each evaluation indicator, and finally a comprehensive quality index is obtained. S7: Based on the comprehensive quality index and the preset threshold, the quality level of the cold-pressed terminal is determined, and its service life under different working conditions is predicted based on simulation and test data.

2. The method according to claim 1, characterized in that, The microstructure indicators include: material compression rate and filling rate of the terminal crimping area, as well as internal air gap rate and wire single filament deformation uniformity obtained by metallographic analysis, wherein the filling rate is defined as the ratio of the metal cross-sectional area of ​​the wire to the inner contour cross-sectional area of ​​the terminal sleeve after crimping.

3. The method according to claim 1 or 2, characterized in that, The electrical performance indicators include: initial contact resistance at the milliohm level and its stability coefficient after a short-term high-current impact, wherein the stability coefficient is the ratio of the resistance value after the impact to the initial value; and steady-state temperature rise under rated current.

4. The method according to claim 1, characterized in that, The mechanical performance indicators include: axial pull-out force, cyclic bending fatigue cycles, and contact normal force measured by a micro-force tester, wherein the contact normal force needs to be measured directly or indirectly at the contact interface under simulated assembly conditions.

5. The method according to claim 1, characterized in that, The environmental tolerance indicators include: the corrosion weight gain rate and contact resistance change rate after salt spray test, and the insulation resistance decrease rate after temperature-humidity-bias current composite test.

6. The method according to claim 1, characterized in that, In step S3, the electro-thermal-mechanical multiphysics coupling simulation specifically involves: using the current load as input, calculating the temperature field caused by Joule heating, then coupling the thermal stress caused by the temperature field with the mechanical stress, analyzing the stress concentration and plastic deformation region of the terminal structure, and simultaneously feeding the temperature field back to the material conductivity for iterative calculation until convergence.

7. The method according to claim 1, characterized in that, In step S4, the accelerated aging profile test is designed using a time-temperature compression model based on failure physics, compressing the actual working conditions of several years into hundreds of hours. The combined stress is applied sequentially in an asynchronous, variable amplitude manner to simulate a real complex environment.

8. The method according to claim 1, characterized in that, In step S6, the specific process of the graded weighted scoring algorithm is as follows: First, set thresholds for four levels—excellent, good, average, and poor—for each indicator; then, determine the indicator level and assign a base score based on the measured or simulated values; next, weight the indicator according to its weight coefficient in the full-dimensional failure model; finally, sum all the weighted scores to obtain a comprehensive quality index between 0 and 100.

9. The method according to claim 1, characterized in that, It also includes step S8: establishing a mapping relationship database of process parameters, quality indicators, and comprehensive quality index of the cold-pressed terminal, and training a model through machine learning methods to back-optimize key process parameters such as crimping mold design, crimping height, and pressure.

10. A quality assessment system for cold-pressed terminals used in implementing the method of any one of claims 1-9, characterized in that, At least including: The system includes a coupled simulation calculation module, an experimental data acquisition module, a digital twin comparison and analysis module, and a comprehensive index calculation and prediction module.

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