Wire harness shielding and connection optimization method

Abstract

The invention relates to a wire harness shielding and connection optimization method in the field of new-generation information technology, and the method comprises the steps: collecting broadband interference data in a wire harness working environment, carrying out the classification processing and feature extraction of different frequency band interferences, and obtaining an interference distribution model of each frequency band; dynamically adjusting shielding structure parameters according to the interference distribution model, enhancing shielding layer density distribution at a high frequency band, and determining optimized shielding structure parameters; if the signal integrity data does not reach a preset signal quality threshold value, performing iterative adjustment on a shielding structure to obtain an updated shielding optimization scheme; performing a multi-scene simulation test on the shielding optimization scheme to determine a final shielding optimization scheme; collecting vibration damage degree and corrosion acceleration data of a wire harness connection part, and analyzing the damage trend of a connection terminal to obtain contact stability risk distribution; and according to the contact stability risk distribution, adjusting terminal anti-corrosion coating parameters to obtain optimized connection design data.

Description

Technical Field

[0001] This invention relates to the field of next-generation information technology, and in particular to a method for optimizing wire harness shielding and connection. Background Technology

[0002] In the fields of modern electronic equipment and new energy vehicles, wiring harnesses, as core components for energy transmission and signal transmission, directly affect the stability and safety of the system. Especially in complex electromagnetic environments and high-frequency signal transmission, the anti-interference capability and connection reliability of wiring harnesses are crucial, becoming a key link in ensuring the normal operation of equipment.

[0003] However, current solutions still have significant shortcomings in addressing these challenges. Existing methods often struggle to adapt to varying interference across different frequency ranges, especially in high-frequency environments where shielding effectiveness declines significantly. Simultaneously, the durability of wire harness connections faces considerable challenges, easily leading to performance degradation after prolonged use. A deeper analysis of this area reveals that the core challenges primarily focus on two aspects. First, wire harness shielding designs lack flexibility in dealing with wide-band interference. Traditional fixed-angle braiding methods cannot simultaneously meet the protection requirements of both low-frequency and high-frequency environments, resulting in poor interference suppression in certain frequency bands. Second, this design limitation further exacerbates the adaptability issues of wire harnesses in complex environments. Especially under high-frequency interference, the decline in shielding effectiveness directly affects signal integrity and can even trigger system failures. These two problems are interconnected; deficiencies in shielding design amplify environmental adaptability shortcomings, thus creating a chain reaction that impacts overall performance.

[0004] Furthermore, the durability of wire harness connections cannot be ignored. During long-term use, even minor vibrations can cause surface damage to the connectors, accelerating the corrosion process and affecting contact stability. This phenomenon is particularly pronounced in harsh environments, becoming a significant factor affecting the lifespan of the wire harness.

[0005] Therefore, how to optimize the wire harness shielding design in a wide frequency range to improve anti-interference capability, while enhancing the durability of connection parts to cope with complex environments, has become a key issue that this research urgently needs to address. Summary of the Invention

[0006] This invention provides a method for optimizing wire harness shielding and connections, mainly including:

[0007] Broadband interference data from the wiring harness operating environment is collected, and interference in different frequency bands is classified and its features are extracted to obtain interference distribution models for each frequency band. Shielding structure parameters are dynamically adjusted based on these models, with enhanced shielding layer density distribution in high-frequency bands to determine optimized shielding structure parameters. These optimized shielding structure parameters are applied to the wiring harness design to simulate interference suppression effects under different environments, obtain signal integrity data, and determine if a preset signal quality threshold is reached. If the signal integrity data does not reach the preset signal quality threshold, the shielding structure is iteratively adjusted to obtain an updated shielding optimization scheme. Multi-scenario simulation tests are performed on the shielding optimization scheme to determine the final shielding optimization scheme. Vibration damage and corrosion acceleration data of the wiring harness connection points are collected, and the damage trend of the connection terminals is analyzed to obtain a contact stability risk distribution. The terminal anti-corrosion coating parameters are adjusted based on the contact stability risk distribution to obtain optimized connection design data. The optimized connection design data is integrated with the final shielding optimization scheme to simulate the comprehensive performance under broadband interference and harsh environments, determining the final wiring harness design parameters. Furthermore, the classification and feature extraction of interference in different frequency bands includes: capturing multi-channel signals through a sensor array to obtain an original interference sequence; converting the original interference sequence to the frequency domain using Fourier transform, separating low-frequency, mid-frequency, and high-frequency interference groups to obtain frequency band interference groups; applying adaptive filtering to the frequency band interference groups, minimizing the squared error by iteratively updating the filter coefficients, with the filter coefficients initially set to zero vectors and gradually adjusting to match the input signal to obtain decomposed signal components; extracting the peak frequency and energy distribution of the amplitude spectrum and phase spectrum from the decomposed signal components, fusing the ambient temperature and humidity data of the harness for pattern matching to obtain an interference feature set; and using Gaussian mixture fitting to fit the parameters of each frequency band based on the interference feature set, verifying the consistency between the model and the collected data, and obtaining the interference distribution model for each frequency band. Furthermore, the step of dynamically adjusting the shielding structure parameters according to the interference distribution model includes: obtaining high-frequency band data from the interference distribution model, separating low-efficiency frequency bands using spectrum analysis to obtain high-frequency interference characteristics; determining density adjustment requirements based on the high-frequency interference characteristics and a preset interference intensity threshold to obtain a density adjustment basis; dynamically adjusting the shielding layer thickness and distribution according to the density adjustment basis to enhance the shielding layer density distribution in the high-frequency band to obtain a preliminary shielding configuration; and integrating the wire harness environmental temperature and humidity factors from the preliminary shielding configuration, verifying the stability of the density distribution through simulated environmental changes, and determining the optimized shielding structure parameters.Furthermore, the step of applying the optimized shielding structure parameters to the harness design and determining whether a preset signal quality threshold has been reached includes: obtaining the harness design basis from the optimized shielding structure parameters; adjusting the structural layout using a method that integrates vibration factors; calculating the layout offset value by integrating vibration amplitude data and parameter correspondence to obtain a preliminary harness configuration; simulating variable environmental conditions for the preliminary harness configuration; separating data based on a preset interference model using interference suppression calculations and frequency band energy comparisons to determine environmental impact indicators; collecting signal integrity samples based on the environmental impact indicators; extracting peak features from the test sequence using spectral analysis to obtain a quantized integrity value; comparing the quantized integrity value with a preset signal quality threshold; if the threshold is exceeded, adjusting the density distribution and recalculating the configuration to determine if the preset signal quality threshold has been reached. Furthermore, if the signal integrity data does not reach the preset signal quality threshold, the shielding structure is iteratively adjusted, including: collecting test data through signal integrity testing, determining that the preset threshold has not been reached, and obtaining the substandard frequency band indicators; comparing environmental factors with frequency band data to determine interference impact assessment based on insufficient environmental adaptability for the substandard frequency band indicators, and obtaining frequency band-specific optimization parameters; integrating vibration interference simulation based on the frequency band-specific optimization parameters, recalculating the shielding layer distribution fusion optimization parameters and vibration simulation data, and obtaining distribution adjustment values; comparing the distribution adjustment values ​​with the quality threshold to generate an updated design scheme, and determining that the signal integrity requirements are met. Furthermore, the multi-scenario simulation test of the shielding optimization scheme includes: simulating various complex environmental conditions for the updated design scheme using a pre-built multi-scenario simulation platform, obtaining response data of the harness under different environmental variables, and determining the preliminary anti-interference performance range; refining the recording of environmental variables with significant interference impact based on the preliminary anti-interference performance range, and obtaining detailed environmental interference distribution characteristics; adjusting and optimizing parameters to adapt to specific environmental variable control requirements by comparing and verifying the environmental interference distribution characteristics with existing shielding layer distribution parameters, and obtaining adjusted shielding layer configuration data; implementing a simulation test process for the adjusted shielding layer configuration data, collecting final data and comparing it with preset thresholds to determine the final shielding optimization scheme. Furthermore, the analysis of the damage trend of the connection terminals includes: collecting historical data on vibration damage and corrosion acceleration at the wire harness connection points, obtaining fatigue monitoring records of the terminal materials, and obtaining a preliminary damage index set; using the Arrhenius corrosion prediction model to analyze the damage trend of the connection terminals based on the preliminary damage index set, wherein the model inputs are the damage index set and time series data, and outputs predicted trend values ​​to obtain trend change curves; extracting the correlation features between corrosion acceleration and vibration damage from the trend change curves, obtaining feature values ​​by calculating the Pearson correlation coefficient, and obtaining a risk impact factor group; obtaining optimization adjustment parameters through simulated load testing based on the risk impact factor group to obtain the potential contact stability risk distribution.Furthermore, the integration of the optimized connection design data with the final shielding optimization scheme includes: performing data-layer fusion between the optimized connection design data and the final shielding optimization scheme to obtain integrated harness model data; simulating electromagnetic field distribution under preset wideband interference conditions for the harness model data to obtain an interference response curve; performing multi-factor durability testing by superimposing harsh environmental parameters on the interference response curve to determine a comprehensive tolerance index; implementing local modifications to the internal structural layout of the harness based on the comprehensive tolerance index to obtain a parameter correction set; and comparing the parameter correction set with a preset performance threshold to determine the final harness design parameters.

[0008] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0009] This invention discloses a method for optimizing the anti-interference and connection durability of wire harnesses. By collecting broadband interference data and establishing an interference distribution model, the method dynamically adjusts shielding design parameters to enhance the density distribution of the high-frequency shielding layer. Simultaneously, it collects data on vibration damage and corrosion acceleration at connection points, analyzes contact stability risks, and optimizes the anti-corrosion coating of the connection terminals. The shielding optimization scheme is integrated with the connection design data to simulate the comprehensive performance of the wire harness in complex environments, yielding the final design parameters. Through iterative optimization and multi-scenario simulation, this invention effectively improves the anti-interference capability and connection durability of wire harnesses in broadband interference and harsh environments, significantly improving the long-term performance and signal integrity of the wire harness, and providing a systematic optimization method for wire harness design. Attached Figure Description

[0010] Figure 1 This is a flowchart of a wire harness shielding and connection optimization method according to the present invention. Detailed Implementation

[0011] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0012] like Figure 1 This embodiment of a wire harness shielding and connection optimization method may specifically include:

[0013] Step S101 involves collecting broadband interference data in the wiring harness working environment, classifying the interference characteristics of different frequency bands, and using an adaptive filtering algorithm to decompose and extract features of the interference signals in real time to obtain the distribution model of interference in each frequency band.

[0014] Broadband interference data was collected using a wiring harness environment, and multi-channel signals were captured using a sensor array to obtain the original interference sequence. Different frequency bands were classified based on the original interference sequence, and the time-domain signal was converted to the frequency domain using Fourier transform to separate low-frequency, mid-frequency, and high-frequency interference groups, resulting in frequency band interference groups. Adaptive filtering was applied to these frequency band interference groups, and the filter coefficients were iteratively updated to minimize the squared error. The filter coefficients were initially set as zero vectors and gradually adjusted to match the input signal, where the reference signal was a preset pure noise template. The error was defined as the difference between the output signal and the reference signal, with the desired output being close to pure interference components, thus obtaining the decomposed signal components. A distribution model was constructed based on the interference feature set, and Gaussian mixture fitting was used to fit the parameters of each frequency band. The consistency between the model and the collected data was verified, resulting in the interference distribution model for each frequency band.

[0015] In one embodiment, the present invention provides an interference signal processing method to address the wideband electromagnetic interference problem existing in the working environment of automotive wiring harnesses. By collecting interference data in actual operation, classifying and adaptively filtering it, an interference distribution model for each frequency band is finally established, thereby providing a basis for the electromagnetic compatibility design of wiring harnesses.

[0016] Specifically, the first step is to collect broadband interference data in the wiring harness's operating environment. During vehicle operation, the wiring harness is subject to interference from multiple sources, including the engine ignition system, motor drive, and external radio signals. This interference covers a wide frequency range, from low to radio frequency. The data collection process uses electromagnetic sensors or oscilloscopes installed near the wiring harness to record voltage or current waveform data in real time.

[0017] For example, in vehicle driving tests, sensors are placed near the wiring harness tethering location, and the sampling rate is set to cover a range of several GHz to ensure the capture of complete wideband interference signals. Based on the collected data, further classification processing is performed according to the interference characteristics of different frequency bands. Wideband interference typically includes low-frequency conducted interference, mid-frequency coupled interference, and high-frequency radiated interference. The classification processing converts the time-domain signal to the frequency domain using Fourier transform to identify the frequency bands where the main energy is concentrated.

[0018] For example, the frequency range is divided into three intervals: 0-1MHz, 1-30MHz, and above 30MHz, corresponding to conduction, near-field coupling, and far-field radiation characteristics, respectively, thus laying the foundation for subsequent targeted processing. In one implementation, an adaptive filtering algorithm is used to decompose and extract features of the interference signal in real time. This is the core of this scheme. The adaptive filtering algorithm can automatically adjust the filter coefficients according to changes in the input signal without prior knowledge of the statistical characteristics of the interference. In a wire harness environment, the interference signal has non-stationary characteristics; therefore, a least mean square (LMS) adaptive filter or its variant is selected for real-time processing.

[0019] Specifically, the algorithm first sets initial filter coefficients, then iteratively updates the coefficients through error signal feedback, gradually bringing the output signal closer to the desired pure interference component, thereby achieving the separation of useful signals from interference. Furthermore, the adaptive filtering process includes two closely related steps: signal decomposition and feature extraction. In the decomposition stage, the filter decomposes the broadband interference signal into multiple sub-band signals, each corresponding to a specific frequency band. Feature extraction calculates parameters such as amplitude spectrum, power spectral density, and peak frequency for each sub-band. For example...

[0020] In one possible implementation, for a given sub-band signal, its root mean square value is calculated as an intensity feature, and phase fluctuations are recorded as time-varying features. These features can reflect the instantaneous distribution of interference in that frequency band. Through real-time iteration, the algorithm can continuously extract features during vehicle operation, ensuring that processing is synchronized with environmental changes.

[0021] Preferably, the Normalized Least Mean Square (NLMS) algorithm can be used as a variant of adaptive filtering to improve convergence speed. In environments with rapidly changing wiring harnesses, NLMS avoids unstable coefficient updates caused by drastic changes in input power through step size normalization, thus better adapting to interference intensity fluctuations caused by engine speed variations. Based on the extracted features, a distribution model for interference in each frequency band is further obtained. The distribution model is constructed through statistical analysis of feature data sequences.

[0022] For example, histogram statistics can be performed on the amplitude feature sequence of a certain frequency band. If it exhibits an approximately Gaussian shape, a Gaussian distribution model is used to fit the mean and variance parameters; if it exhibits Rayleigh distribution characteristics, a Rayleigh model is used accordingly. This model can quantify the probability distribution characteristics of interference in that frequency band. In another implementation, for wiring harness scenarios dominated by high-frequency radiation interference, finer sub-bands can be prioritized, such as every 10MHz interval, and Kalman filtering can be combined with an adaptive process to further improve feature extraction accuracy. Kalman filtering takes the time-series data of the interference signal as input and outputs an estimated interference state. Through iterative updates of prediction and correction, the adaptive filter dynamically adjusts parameters to optimize the tracking and suppression of spike interference. This approach is suitable for high-voltage wiring harness environments in electric vehicles, where spike interference generated by switching power supplies requires higher resolution processing.

[0023] It should be noted that the establishment of interference distribution models for each frequency band using the above methods can provide a quantitative basis for wire harness shielding design.

[0024] For example, if a model shows that the interference intensity of a certain frequency band follows a specific distribution, the probability of exceeding a threshold can be calculated, thereby guiding the selection of the shielding layer thickness.

[0025] For example, by applying this solution in actual vehicle road tests, real-time monitoring and modeling of wiring harness interference can be achieved, and the resulting distribution model directly supports the verification process of electromagnetic compatibility standards.

[0026] Step S102: Based on the obtained interference distribution model, to address the problem of poor high-frequency performance, dynamically adjust the parameter configuration of the shielding design method, enhance the density distribution of the shielding layer in the high-frequency band, and determine the optimized shielding structure parameters.

[0027] High-frequency data is obtained from an interference distribution model, and low-efficiency frequency bands are separated using spectral analysis to obtain high-frequency interference characteristics. Shielding effectiveness is evaluated based on these high-frequency interference characteristics. Density adjustment requirements are determined by comparing the shielding to a preset interference intensity threshold (set to 50dB based on electromagnetic compatibility standards), thus obtaining the basis for density adjustment. The shielding layer thickness and distribution are dynamically adjusted according to this density adjustment basis to enhance the shielding density distribution in the high-frequency bands, resulting in a preliminary shielding configuration. The preliminary shielding configuration is then integrated with the ambient temperature and humidity factors of the wiring harness. The stability of the density distribution is verified by simulating environmental changes, and the optimized shielding structure parameters are determined.

[0028] In one implementation, the shielding effectiveness of automotive wiring harnesses in the high-frequency band is evaluated and optimized based on a previously established interference distribution model. This model provides the probability distribution characteristics of interference in each frequency band, such as the amplitude and peak frequency data of high-frequency radiated interference. By analyzing this data, specific manifestations of poor high-frequency effectiveness are identified, such as insufficient shielding attenuation leading to signal leakage in frequency bands above 30MHz.

[0029] It should be noted that the interference distribution model is used as the input basis here to quantify the intensity and distribution pattern of high-frequency interference, thereby guiding subsequent adjustments.

[0030] Specifically, to address the issue of poor high-frequency performance, a dynamic adjustment mechanism is employed to modify the parameter configuration of the shielding design. This adjustment is based on interference statistics parameters output by the model, such as calculating the average power spectral density in the high-frequency band, to identify the weaknesses of the current shielding structure. The dynamic adjustment process involves real-time monitoring of interference changes during vehicle operation and updating parameters based on model predictions.

[0031] For example, in the context of electric vehicle wiring harnesses, if the model shows that high-frequency interference follows a Rayleigh distribution, the proportion of conductive material in the shielding layer is increased accordingly to enhance the absorption capacity against radiated interference. This mechanism ensures that adjustments are synchronized with the actual interference environment, avoiding the limitations of static design. Furthermore, enhancing the density distribution of the shielding layer at high frequencies is achieved by optimizing the material layout. Shielding density refers to the concentration of shielding material per unit area; for example, increasing the density of the metal mesh in bending areas of the wiring harness where high frequencies are susceptible.

[0032] For example, in one possible implementation, the density is increased from 1.2 times to 1.5 times the standard value by utilizing the peak frequency characteristics of the model, thereby locally enhancing a specific high-frequency range, such as 100MHz to 1GHz. This enhancement helps reduce the penetration of electromagnetic waves and improves overall compatibility.

[0033] Preferably, determining the optimized shielding structure parameters involves a comprehensive evaluation of the adjustment results. The enhanced density distribution is input into simulation tools to verify its suppression effect on high-frequency interference, for example, by comparing the interference attenuation values ​​before and after adjustment.

[0034] In one embodiment, in the testing of hybrid vehicle wiring harnesses, the optimized parameters include a shielding layer thickness of 0.5 mm and a density index of 85%. These parameters are directly derived from model analysis to ensure that the structure can adapt to various operating scenarios.

[0035] Understandably, the optimization process begins with model application, progresses to parameter tuning and density enhancement, and ultimately outputs determined parameters, forming a closed chain. In practical applications, this method can be implemented on vehicle assembly lines, providing quantifiable evidence for shielding improvements.

[0036] For example, in the scenario of wiring harnesses for gasoline-powered vehicles, to address high-frequency interference near the engine, the model guides the concentrated distribution of shielding layer density in key sections. Once the parameters are determined, the interference can be reduced to 70% of its original level. This approach expands the applicability of the technical solution.

[0037] It should be noted that the core of dynamic adjustment lies in the iterative interaction between the model and the design method. For example, configuration parameters are updated through feedback loops to avoid the recurrence of poor high-frequency performance. In another implementation, for long-distance harnesses, uniformity of distribution is considered when increasing density, and optimized parameters include multi-layer shielding structures to cover a wide high-frequency range. Furthermore, the technical goal of this process is to improve the electromagnetic compatibility of the harness, achieving stable interference suppression through precise parameter determination.

[0038] For example, in a test environment, the optimized parameters were applied to a prototype harness to verify the performance improvement in the high-frequency band.

[0039] Step S103: By applying the optimized shielding structure parameters to the wiring harness design, the interference suppression effect under different environments is simulated, the signal integrity test data is obtained, and it is determined whether the preset signal quality threshold is reached.

[0040] The wiring harness design is based on the optimized shielding structure parameters. The structural layout is adjusted by incorporating vibration factors, with the vibration factors and amplitude data derived from the S101 experimental test. The layout offset is calculated by integrating the vibration amplitude data with the parameter correspondence, resulting in a preliminary wiring harness configuration. For this preliminary configuration, variable environmental conditions are simulated, and key frequency band data is separated through interference suppression calculations. These calculations are based on comparing the frequency band energy with the interference distribution model of each frequency band in S101, i.e., a preset interference model, to determine environmental impact indicators. Signal integrity samples are collected based on these environmental impact indicators. The test sequences are processed using spectrum analysis tools. By converting the sample sequences to the frequency domain and extracting peak features, a quantified integrity value is obtained. This quantified integrity value is compared to a preset signal quality threshold of 0.95. If the value is lower than the threshold, the density distribution is iteratively adjusted by increasing the high-frequency shielding layer spacing ratio and recalculating the configuration until the preset signal quality threshold is reached.

[0041] In one implementation, the optimized shielding structure parameters are applied to the harness design by integrating the parameters into the design process.

[0042] Specifically, these parameters include shielding thickness, density distribution, and material proportions, previously derived through interference model analysis. These parameters are then imported into wiring harness design software, such as in electric vehicle wiring harness layouts, to adjust the shielding configuration in high-voltage cable sections, ensuring the parameters match the wiring harness geometry. This application process considers the overall structure of the wiring harness, for example, applying higher density parameters at bends to accommodate the vehicle's vibration environment.

[0043] It should be noted that compatibility verification is necessary when applying parameters. Preliminary modeling should be used to check for conflicts with existing wiring harness components, forming the basis of the design blueprint. Furthermore, simulating interference suppression effects under different environments involves using electromagnetic simulation tools to reproduce various scenarios.

[0044] For example, in a hybrid vehicle environment, the simulation includes low-frequency interference during urban road driving and high-frequency radiation on highways. A harness model based on optimized parameters is placed into the simulation environment, setting environmental variables such as temperature changes and external electromagnetic field strength. By running the simulation, the response of the shielding structure to interference is observed, for example, tracing signal attenuation curves in the 30MHz to 1GHz frequency band. This simulation process relies on the finite element analysis method, progressively inputting different environmental parameters to cover various operating conditions, ensuring that the simulation results reflect the actual interference distribution.

[0045] Preferably, the test data for signal integrity are obtained through a combination of laboratory testing and field verification.

[0046] In one possible implementation, the wiring harness is first assembled and optimized in a controlled environment, such as in the engine compartment of a gasoline-powered vehicle, and then the signal transmission characteristics are measured using a vector network analyzer. The test data includes eye diagram parameters, insertion loss, and reflection loss, which are collected from both ends of the wiring harness.

[0047] Specifically, the testing process is executed in stages. First, simulated interference signals are injected, and then the integrity metrics of the output signal are recorded, such as evaluating the packet loss rate under high-frequency interference. This data acquisition emphasizes repeatability, obtaining reliable results by averaging multiple trials.

[0048] It is understandable that the determination of whether the preset signal quality threshold has been reached is based on the comparison logic of the collected data.

[0049] In one embodiment, preset thresholds are defined as signal attenuation not exceeding 20 dB and bit error rate below 10⁻⁶, these thresholds are derived from industry standards. Test data is compared item by item with the thresholds, for example, using software tools to automatically calculate deviation values. If the data meets all thresholds, the design is deemed acceptable; otherwise, non-compliance items are recorded to guide further iterations. This judgment process is integrated into the verification process to ensure that the harness design is adaptable to different environments. In another embodiment, for the design application of long-distance harnesses, the simulated environment is extended to extreme conditions such as high-temperature or humid scenarios. After the parameters are applied, data is acquired through multiple rounds of simulation, such as simulating interference near an electric vehicle battery pack to test signal integrity. When judging the thresholds, the impact of dynamic factors such as changes in vehicle speed on the data is considered to form a comprehensive evaluation. Furthermore, the technical goal of this process is to verify the effective integration of parameters, for example, in hybrid power harnesses, to confirm interference suppression stability through simulation and testing.

[0050] For example, in the testing of wiring harnesses for gasoline-powered vehicles, parameters are applied to simulate urban congestion environments, data is acquired, and thresholds are determined, with an emphasis on data accuracy throughout the process.

[0051] Step S104: If the signal integrity test data does not reach the preset threshold, the shielding design method is adjusted in a second iteration. For frequency bands with insufficient environmental adaptability, the shielding layer distribution is recalculated to obtain an updated design scheme.

[0052] The test data is collected through signal integrity testing to determine whether a preset threshold has been reached, thus identifying the non-compliant frequency band indicators. A secondary adjustment process is then implemented for these non-compliant frequency band indicators. An interference impact assessment is obtained from insufficient environmental adaptability, and frequency band optimization parameters are determined by comparing environmental factors with frequency band data. Based on these optimization parameters, vibration interference simulations are integrated with the test data to recalculate the shielding layer distribution. The distribution adjustment value is obtained by fusing the optimization parameters with the vibration simulation data. This distribution adjustment value is then compared with a quality threshold (a preset shielding quality standard threshold of 0.95) to generate an updated design scheme, determining whether the signal integrity requirements have been met.

[0053] In one implementation, if the signal integrity test data does not reach a preset threshold, the process of making a second iteration adjustment to the shielding design method first identifies the problem through data analysis.

[0054] Specifically, this adjustment is based on signal attenuation curves and bit error rate metrics collected from previous tests to analyze which frequency bands are not environmentally adaptable, such as evaluating low-frequency interference bands in urban roads in electric vehicle wiring harnesses.

[0055] It should be noted that frequency bands with insufficient environmental adaptability refer to those ranges where signal quality degrades significantly during simulation or testing, such as the 20MHz to 500MHz range, which is determined by comparing test data with the threshold deviation.

[0056] For example, in the wiring harness design of hybrid vehicles, if tests show poor high-frequency interference suppression, specific parameters for these frequency bands are recorded, such as increased attenuation due to insufficient shielding thickness, forming the basis for iteration. Furthermore, for frequency bands with insufficient environmental adaptability, recalculating the shielding distribution involves using an interference model to optimize the parameter distribution. In one possible implementation, this calculation process first reviews the initial shielding structure parameters, such as layer thickness and density, and then adjusts them according to the interference characteristics of the insufficient frequency bands.

[0057] For example, in the bending parts of the wiring harness of a gasoline vehicle, if the low-frequency band has poor adaptability, the shielding density of that frequency band can be increased through model simulation. The calculation method includes evaluating the interference intensity and the impedance matching of the shielding material, and gradually adjusting the distribution to cover the insufficient area.

[0058] Understandably, the principle behind recalculating the shielding layer distribution is to balance the overall structure and ensure that the wiring harness maintains signal integrity under vibration or temperature changes.

[0059] Specifically, this process is broken down into steps: first, input the data of the insufficient frequency band into the model, analyze the interference propagation path, and then redistribute the shielding layer according to the path characteristics, such as increasing the material proportion in high-voltage cable sections to enhance the suppression effect. This calculation emphasizes iteration, verifying through multiple simulations whether the adjusted distribution improves adaptability. For example, in wiring harnesses near electric vehicle battery packs, a more uniform density distribution is calculated to address the insufficient mid-frequency band in humid environments, avoiding local weaknesses.

[0060] Preferably, this calculation process is aided by software tools to automate parameter optimization and generate a quantifiable distribution scheme. In another embodiment, the updated design scheme is obtained by integrating the recalculated shielding layer distribution into the harness blueprint.

[0061] For example, in the overall layout of hybrid vehicles, the updated scheme includes adjusting the configuration of the shielding layer in different sections to ensure it matches the vehicle's dynamic environment.

[0062] It should be noted that this update takes into account compatibility verification, such as checking whether the new distribution conflicts with existing components, and generating the final solution after confirmation through preliminary modeling.

[0063] Specifically, the technical goal of the updated design is to improve the interference suppression stability of the wiring harness. For example, in high-speed road simulations, it is confirmed that the signal quality after adjustment reaches a threshold, thereby supporting subsequent production applications.

[0064] For example, iterative adjustments for long-distance harnesses.

[0065] In one embodiment, if test data shows insufficient frequency band performance under extreme temperatures, the focus is recalculated to optimize material proportions. The resulting solution is then validated in the laboratory to confirm its effectiveness. This process ensures the versatility of the design, adapting to various environmental scenarios within the same automotive wiring harness field. Furthermore, this overall process of secondary iterative adjustments emphasizes data-driven approaches. For example, in the engine compartment wiring harness of a gasoline-powered vehicle, the distribution is cyclically calculated based on test feedback, and the resulting updated solution can be directly applied to the next simulation. This method achieves continuous improvement in shielding design through targeted adjustments.

[0066] Step S105: By conducting multi-scenario simulation tests on the updated design scheme, data on the anti-interference capability of the wiring harness in complex environments are collected to determine the final shielding optimization scheme.

[0067] Using a pre-built multi-scenario simulation platform, the updated design scheme is simulated under various complex environmental conditions to obtain response data of the wiring harness under different environmental variables, thus determining a preliminary anti-interference performance range. Based on this preliminary anti-interference performance range, a simulation data analysis module is used to refine the recording of environmental variables with significant interference effects, obtaining detailed environmental interference distribution characteristics and determining their specific impact range on the wiring harness. By comparing and verifying the environmental interference distribution characteristics, optimization parameter sources are extracted from the preliminary range and interference characteristics. Combined with existing parameters of the shielding layer distribution, the optimization parameters are adjusted to adapt to specific environmental variable control requirements, resulting in adjusted shielding layer configuration data. For the adjusted shielding layer configuration data, a simulation test process is implemented to verify its anti-interference capability in a multi-scenario simulation environment. The final data is collected and compared with preset thresholds to determine the final shielding optimization scheme.

[0068] In one implementation, the process of conducting multi-scenario simulation tests on the updated design first involves establishing simulation models for various actual automotive operating environments.

[0069] Specifically, this test utilizes electromagnetic compatibility simulation software to construct a three-dimensional model of the wiring harness and incorporates interference sources under different vehicle operating conditions, such as low-frequency electromagnetic noise from urban roads, high-frequency radiation from highways, and the high-temperature vibration environment of the engine compartment. By setting these scenarios, the performance of the updated shielding layer distribution under complex conditions can be comprehensively evaluated.

[0070] It should be noted that the selection of multiple scenarios is based on common electromagnetic interference types in automotive wiring harnesses, ensuring that the test covers typical usage conditions.

[0071] For example, in the design verification of high-voltage wiring harnesses for electric vehicles, simulation tests include mid-frequency interference scenarios in a humid environment near the battery pack and transient electromagnetic pulse scenarios during fast charging. This combination of multiple scenarios can simulate the superimposed interference that the wiring harness may encounter in actual vehicle operation, thereby verifying the robustness of the shielding design. Furthermore, the response of the wiring harness is observed by applying virtual interference signals during the simulation test.

[0072] Specifically, the software takes the updated shielding layer thickness, material distribution, and weaving density parameters as input, and then runs an electromagnetic field solver for each scenario to calculate the attenuation and crosstalk values ​​on the signal transmission path.

[0073] Understandably, this simulation method avoids the repeated production of physical prototypes and enables rapid iterative verification.

[0074] In one embodiment, for the power transmission harness of hybrid vehicles, the test scenario specifically focuses on electromagnetic compatibility under switching conditions, such as low-frequency vibration coupling interference during internal combustion engine startup and radio frequency interference during high-voltage inverter operation. By running multiple scenarios in parallel, signal integrity data of each segment of the harness is acquired, forming a comprehensive basis for evaluating interference immunity.

[0075] Preferably, collecting data on the anti-interference capability of the wiring harness in complex environments involves monitoring multiple key indicators.

[0076] Specifically, these data include eye diagram width, signal attenuation curve, crosstalk coefficient, and bit error rate. The eye diagram width reflects the time-domain characteristics of the signal quality, while the attenuation curve shows the loss in the frequency domain. In the simulation output, these metrics are recorded in real-time using probe points to ensure a direct correlation between the data and the shielding layer distribution.

[0077] For example, in testing the wiring harness in the engine compartment of a gasoline-powered vehicle, the data acquisition process focuses on recording crosstalk data in the high-frequency band under high-temperature conditions, as well as low-frequency noise penetration under vibration conditions. This targeted acquisition helps identify remaining weak frequency bands. Based on the collected anti-interference capability data, the final shielding optimization scheme is determined by comparing the indicators under various scenarios with preset thresholds.

[0078] Specifically, if the data for all scenarios meets the threshold requirements, the current update scheme is directly adopted as the final optimization scheme; otherwise, the scenarios that do not meet the requirements are recorded, and the aforementioned iterative adjustment is returned. In another implementation, after multi-scenario testing of long-distance wiring harnesses, data analysis shows that the anti-interference capability is weakest under complex urban road conditions. In this case, the final scheme retains the shielding distribution configuration optimized for this scenario to ensure the applicability of the overall design in various automotive environments.

[0079] Step S106: To address the connection durability issue, historical data on vibration damage and corrosion acceleration are collected from the wire harness connection points. A corrosion prediction model is used to analyze the damage trend of the connection terminals to obtain the potential contact stability risk distribution.

[0080] Historical data on vibration damage and corrosion acceleration were collected at the wire harness connection points, and fatigue monitoring records of the terminal materials were obtained to obtain a preliminary damage index set. Based on this preliminary damage index set, the Arrhenius corrosion prediction model was used to analyze the damage trend of the connection terminals. This model integrates non-temperature variables through the extended formula A=A0*exp(-Ea / RT)*f(V,C), where A is the acceleration factor, A0 is a constant, Ea is the activation energy, R is the gas constant, T is the temperature, and f(V,C) is a correction function for vibration V and corrosion C. The inputs are the damage index set and time series data, and the output is the predicted trend value. The trend change curve was obtained to determine the potential contact stability risk level. From the trend change curve, the correlation characteristics between corrosion acceleration and vibration damage were extracted, and the feature values ​​were obtained by calculating the Pearson correlation coefficient to obtain a risk impact factor group and determine the terminal durability attenuation distribution. Based on the risk impact factor group, the stability of the wire harness connection points was verified. Initial parameters for simulated load testing were set using the risk impact factor group, and simulated load testing was conducted to obtain optimized adjustment parameters, resulting in the potential contact stability risk distribution.

[0081] In one implementation, to address the issue of connection durability, it is first necessary to understand how connection durability manifests itself in automotive wiring harnesses.

[0082] Specifically, connection durability issues typically stem from mechanical stresses and environmental factors experienced by wiring harness connections during vehicle operation, such as loosening due to vibration or poor contact caused by corrosion. These problems affect the reliability of signal transmission, thus requiring a systematic approach to assess and predict potential risks.

[0083] It should be noted that the connection durability assessment is based on the physical structure of the wiring harness, including terminals, connectors, and sealing assemblies, which are exposed to various stresses under different automotive operating conditions. This provides a foundation for subsequent analysis. Collecting historical data on vibration damage and corrosion acceleration from the wiring harness connection points is a crucial step.

[0084] For example, at the connection points of automotive wiring harnesses, such as the interface between the dashboard and sensors, the data acquisition process involves reviewing vehicle maintenance records and test logs.

[0085] Specifically, vibration damage is quantified by recording acceleration data of the connection points during road testing. For example, accelerometers are used to monitor peak vibration values ​​generated during vehicle movement, and a cumulative damage index is calculated. Corrosion acceleration is obtained from historical environmental exposure data, such as humidity, temperature, and salt spray test results, which are derived from the manufacturer's durability testing database.

[0086] Understandably, this data collection ensures that the data covers the actual use of the wiring harness in urban roads and off-road environments, thus forming a comprehensive historical dataset. Furthermore, the collection of vibration damage can be broken down into multiple stages.

[0087] In one embodiment, for the battery connection harness of an electric vehicle, historical data is obtained from the vehicle's dashcam and maintenance records, specifically including damage values ​​measured in vibration tests. These values ​​are derived using the integral vibration energy formula, but do not involve specific numerical calculations; instead, the focus is on the accumulation of data trends.

[0088] Preferably, historical data on corrosion acceleration is supplemented by accelerated aging tests in the laboratory, such as simulating environments exposed to rainwater and pollutants, recording changes in the surface oxidation degree of the connection terminals. This phased data collection helps build a reliable data foundation for model input. Analyzing the damage trend of the connection terminals using a corrosion prediction model is the core process.

[0089] Specifically, the corrosion prediction model is a machine learning-based framework used to simulate the degradation path of connection terminals under future environments. The model first integrates collected historical data as input, and then identifies key variables, such as vibration damage and corrosion acceleration indices, through a feature extraction module.

[0090] It should be noted that the principle of the model lies in using regression algorithms to fit the damage trend curve, such as linear regression or more advanced neural network structures, but the key is the logic of the process: the model learns patterns from historical data during the training phase, and the prediction phase uses current data to generate the trend curve.

[0091] In one possible implementation, for wiring harness connections in hybrid vehicles, the model analysis process includes data preprocessing steps, such as normalizing vibration and corrosion data, followed by applying a model to calculate predicted values ​​for terminal resistance variations. This analysis reveals acceleration points in damage trends, thereby identifying high-risk periods.

[0092] For example, the model framework can be decomposed into an input layer, a hidden layer, and an output layer, where the input layer receives historical data, the hidden layer processes nonlinear relationships, and the output layer generates a trend distribution map. This modular structure enables the model to handle complex combinations of environmental variables, ensuring the accuracy of predictions. In another implementation, the corrosion prediction model's analysis is further extended to multivariate scenarios.

[0093] Specifically, for the engine wiring harness connection of gasoline vehicles, after integrating vibration and corrosion data, the model performs trend simulation: first, an initial state model of terminal damage is established, and then the parameters based on historical acceleration are iteratively updated to gradually derive the slope change of the damage curve.

[0094] Understandably, this iterative process is similar to time series analysis, focusing on how vibration accelerates the corrosion rate to derive a terminal lifetime prediction curve. Based on the analysis results, the potential contact stability risk distribution is obtained.

[0095] Specifically, risk distribution is achieved by mapping damage trends to the spatial location of the connection terminals, for example, by generating a heat map to show high-risk areas.

[0096] In one embodiment, for connections in long-distance harnesses, the distribution map highlights terminals with high vibration damage and marks points of stability degradation caused by accelerated corrosion. This distribution provides a visual basis for risk assessment.

[0097] Preferably, in the overall design of automotive wiring harnesses, this risk distribution can be combined with the material selection for connection points.

[0098] For example, in the implementation of electric vehicle charging interfaces, distribution analysis shows that certain terminals exhibit a stronger corrosion trend, thus guiding targeted reinforcement. Furthermore, obtaining the distribution of contact stability risks involves data visualization steps.

[0099] Specifically, software tools are used to convert the model output into a risk level map, where different colors represent stability levels, ensuring the practicality of the distribution.

[0100] Step S107: Based on the risk distribution of contact stability, adjust the anti-corrosion coating parameters of the terminal material for the connection parts in high-risk areas, obtain optimized connection design data, and determine whether it meets the requirements for long-term use.

[0101] Based on the thermal risk distribution map generated from the contact stability risk distribution, current status data is collected from the terminal material layer for high-risk areas to obtain regional risk values. This determines the priority ranking of connection points and yields a preliminary adjustment range table. Based on this preliminary adjustment range table, and combined with historical records of the anti-corrosion coating and regional risk values, coating parameter values ​​are adjusted to obtain parameter optimization groups. Coating configuration schemes suitable for different areas are then determined. Through these parameter optimization groups, the terminal material layer is simulated and verified to obtain data on changes in material durability, resulting in an optimized connection design. Using this connection design, long-term usability is compared with preset usability standards to determine if the long-term usability requirements are met. If met, the final verification result is obtained; otherwise, the process returns to the parameter optimization group for iterative adjustments until the requirements are met.

[0102] Based on the risk distribution of contact stability, adjusting the anti-corrosion coating parameters of the terminal material for connection parts in high-risk areas is a key step in optimizing the design.

[0103] Specifically, high-risk areas marked in the risk distribution typically correspond to connection terminals subjected to intense vibration or severe environmental exposure, such as wiring harness interfaces in the engine compartment or near the chassis. The contact stability of these areas is susceptible to corrosion, thus requiring adjustments to coating parameters to improve durability. In one implementation, the specific locations of the high-risk areas are first identified.

[0104] Understandably, the risk distribution is presented in the form of a heat map, with different colors corresponding to different risk levels. Engineers select connection terminals with risk values ​​higher than the preset threshold as adjustment targets based on this map.

[0105] For example, in the engine wiring harness connections of gasoline-powered vehicles, high-risk areas are often concentrated near the terminals close to the exhaust system. Addressing these high-risk areas involves adjusting the anti-corrosion coating parameters of the terminal materials, primarily modifying the coating thickness, material composition, and coating process.

[0106] It should be noted that anti-corrosion coatings typically employ tin plating, gold plating, or polymer protective layers. The core of parameter adjustment lies in enhancing resistance to oxidation and electrochemical corrosion.

[0107] Specifically, for tin plating, the plating thickness can be increased or the proportion of added elements in the tin alloy can be optimized to reduce the corrosion rate.

[0108] For example, in the high-voltage battery harness connection terminals of an electric vehicle, if the risk distribution indicates a high corrosion trend in the charging interface area, the original tin plating thickness is increased from the standard value to a higher range, while a small amount of silver is introduced to form a tin-silver alloy coating. This adjustment is achieved through an electroplating process, with process parameters including extended current density and plating time, to ensure uniform coating adhesion and improved density.

[0109] Understandably, this parameter change directly targets environments with high corrosion acceleration, extending the protection cycle of the terminal surface.

[0110] Preferably, in another embodiment, the adjustment of the power control unit wiring harness connection of a hybrid vehicle may employ a composite coating strategy.

[0111] Specifically, the basic tin plating is retained first, and then a nanoscale polymer sealing coating is added. The parameters are adjusted by setting the polymer thickness and curing temperature. This composite structure not only resists salt spray corrosion but also mitigates the propagation of microcracks caused by vibration, thus comprehensively improving the stability of high-risk areas. Further, after adjusting the coating parameters, optimized connection design data is obtained. This process includes writing the new parameters into design drawings or digital models, such as updating terminal specification descriptions in CAD files or refreshing the material property library in simulation software, generating a complete design dataset containing the optimized coating. Based on the optimized connection design data, long-term usability is assessed.

[0112] Specifically, the determination is achieved through durability simulation or accelerated life testing. For example, the optimized design is input into finite element analysis software to simulate the changes in corrosion depth and contact resistance under years of driving conditions. If the results show that the increase in resistance is within the specified threshold, then the long-term usability requirements are met.

[0113] For example, in the optimization of wiring harnesses for long-haul commercial vehicles, after the above adjustments and judgments, the optimized design data showed that the terminals in high-risk areas still maintained stable contact after simulating 10 years of use, thus confirming the feasibility of the solution.

[0114] Step S108: By integrating the optimized connection design data with the shielding optimization scheme, the overall performance of the wire harness under wideband interference and harsh environments is simulated to obtain the final wire harness design parameters.

[0115] Based on the shielding optimization scheme obtained from the aforementioned electromagnetic compatibility analysis, the connection design data and the shielding optimization scheme are fused at the data layer to obtain integrated harness model data. For the harness model data, electromagnetic field distribution is simulated under preset wideband interference conditions to obtain interference response curves. Using the interference response curves, multi-factor durability testing is conducted by superimposing harsh environmental parameters to determine the comprehensive endurance index. Based on the comprehensive endurance index, local modifications are made to the internal structural layout of the harness to obtain a parameter correction set. The parameter correction set is compared with preset performance thresholds to determine the final harness design parameters; if the thresholds are not met, the process returns to the correction step for iterative optimization until they are met.

[0116] In one implementation, the shielding optimization scheme refers to the design of a protection strategy against external interference to the wiring harness. This mainly includes the selection and structural layout of shielding materials, such as using aluminum foil or braided mesh as the shielding layer to block electromagnetic wave intrusion. By integrating the optimized connection design data with this shielding optimization scheme, the electromagnetic compatibility of the wiring harness system is improved. Furthermore, the stability and reliability of the system are verified through comprehensive performance evaluation under simulated broadband interference and harsh environments.

[0117] Specifically, the integration process first imports the connection design data, including terminal specifications and coating parameters, into electromagnetic simulation software. Then, the shielding scheme model file is overlaid to form a complete digital model of the wiring harness. This integration ensures coordination between the connection points and the shielding layer, preventing signal attenuation or interference amplification. In the design of instrument panel wiring harnesses for gasoline-powered vehicles, the integrated model can simulate changes in the electromagnetic environment during vehicle operation.

[0118] Preferably, the integration of the shielding optimization scheme involves parameter matching and adjustment.

[0119] Specifically, shielding solutions are typically optimized based on the frequency response characteristics of the harness. For example, for wideband interference, which is a continuous spectrum from low-frequency magnetic fields to high-frequency radio frequencies, the attenuation effect is enhanced by adjusting the thickness or coverage of the shielding layer.

[0120] It should be noted that broadband interference in the automotive environment originates from the engine ignition system or external wireless signals. During integration, it is necessary to ensure that the resistance value of the connection design data matches the impedance of the shielding layer to reduce reflection loss.

[0121] For example, in the drive motor wiring harness of an electric vehicle, optimized connection data is integrated with a double-layer shielding scheme. The inner layer of the shielding layer uses a copper mesh, and the outer layer is polymer insulation to cope with pulse interference generated by the battery pack. Furthermore, based on the integrated model, the overall performance of the wiring harness under broadband interference and harsh environments is simulated. This simulation process is performed using finite element analysis software. First, an interference source model is defined, such as setting the amplitude and frequency distribution of broadband electromagnetic waves, and then harsh environmental factors, such as high temperature, humidity, or vibration conditions, are superimposed.

[0122] Specifically, harsh environment simulation includes temperature cycling tests and salt spray exposure scenarios, which can affect the insulation performance and shielding effectiveness of the wiring harness.

[0123] In one embodiment, for the control harness of a hybrid electric vehicle, after inputting integrated data into the simulation software, multi-field coupling analysis is run to evaluate signal integrity under interference and material degradation in the environment. Through iterative calculations, changes in the transmission loss and error rate of the harness are observed to ensure that performance indicators are within thresholds.

[0124] Understandably, such simulations can objectively assess the overall durability of the harness. For example, under wideband interference, the shielding optimization scheme can effectively suppress noise coupling, while harsh environment simulations can verify the stability of the connection parts.

[0125] For example, in the design of communication harnesses for long-haul commercial vehicles, simulation results show that the bit error rate of the integrated system is reduced under rain, snow and radio interference, thus confirming the applicability of the design.

[0126] Specifically, the final harness design parameters are obtained by refining the simulation results. Furthermore, the simulation data is exported as a parameter table, including parameters such as 95% shielding coverage, connection resistance threshold of less than 0.1 ohms, and environmental tolerance limit of -40 to 85 degrees Celsius. These parameters are then updated in the design document to form a complete harness specification.

[0127] In one possible implementation, for the charging harness of pure electric vehicles, the final parameters emphasize the optimization of the grounding method of the shielding scheme to enhance wide-band protection, while adjusting the insulation thickness in combination with harsh environment simulation to ensure long-term reliability.

[0128] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several improvements and additions without departing from the principle of the present invention, and these improvements and additions should also be considered within the scope of protection of the present invention.

Claims

1. A method for optimizing wire harness shielding and connections, characterized in that, include: Broadband interference data in the working environment of the wire harness is collected, and interference in different frequency bands is classified and its features are extracted to obtain interference distribution models for each frequency band. The shielding structure parameters are dynamically adjusted according to the interference distribution models, and the shielding layer density distribution is enhanced in the high-frequency band to determine the optimized shielding structure parameters. The optimized shielding structure parameters are applied to the wire harness design to simulate the interference suppression effect under different environments, obtain signal integrity data, and determine whether the preset signal quality threshold is reached. If the signal integrity data does not reach the preset signal quality threshold, the shielding structure is iteratively adjusted to obtain an updated shielding optimization scheme. The shielding optimization scheme was subjected to multi-scenario simulation tests to determine the final shielding optimization scheme; Data on vibration damage and corrosion acceleration at wire harness connection points were collected, and damage trends at connection terminals were analyzed to obtain the risk distribution of contact stability. The terminal anti-corrosion coating parameters are adjusted according to the contact stability risk distribution to obtain optimized connection design data; The optimized connection design data is integrated with the final shielding optimization scheme to simulate the comprehensive performance under broadband interference and harsh environments, and to determine the final harness design parameters.

2. The method for optimizing wire harness shielding and connection as described in claim 1, characterized in that, The classification and feature extraction of interference in different frequency bands includes: capturing multi-channel signals through a sensor array to obtain an original interference sequence; converting the original interference sequence to the frequency domain using Fourier transform, separating low-frequency, mid-frequency, and high-frequency interference groups to obtain frequency band interference groups; applying adaptive filtering to the frequency band interference groups, minimizing the squared error by iteratively updating the filter coefficients, with the filter coefficients initially set to zero vectors and gradually adjusting to match the input signal to obtain decomposed signal components; extracting the peak frequency and energy distribution of the amplitude spectrum and phase spectrum from the decomposed signal components, fusing the ambient temperature and humidity data of the wiring harness for pattern matching to obtain an interference feature set; and using Gaussian mixture fitting to fit the parameters of each frequency band based on the interference feature set, verifying the consistency between the model and the collected data, and obtaining the interference distribution model for each frequency band.

3. The method for optimizing wire harness shielding and connection as described in claim 1, characterized in that, The step of dynamically adjusting the shielding structure parameters according to the interference distribution model includes: obtaining high-frequency band data from the interference distribution model, separating low-efficiency frequency bands using spectrum analysis to obtain high-frequency interference characteristics; determining density adjustment requirements based on the high-frequency interference characteristics and a preset interference intensity threshold to obtain a density adjustment basis; dynamically adjusting the shielding layer thickness and distribution according to the density adjustment basis to enhance the shielding layer density distribution in the high-frequency band to obtain a preliminary shielding configuration; and integrating the wire harness environmental temperature and humidity factors from the preliminary shielding configuration, verifying the stability of the density distribution through simulated environmental changes, and determining the optimized shielding structure parameters.

4. The method for optimizing wire harness shielding and connection as described in claim 1, characterized in that, The step of applying the optimized shielding structure parameters to the harness design and determining whether a preset signal quality threshold has been reached includes: obtaining harness design basis from the optimized shielding structure parameters; adjusting the structural layout using a method that integrates vibration factors; calculating the layout offset value by integrating vibration amplitude data and parameter correspondence to obtain a preliminary harness configuration; simulating variable environmental conditions for the preliminary harness configuration; separating data based on a preset interference model using interference suppression calculations and frequency band energy comparisons to determine environmental impact indicators; collecting signal integrity samples based on the environmental impact indicators; extracting peak features from the test sequence using spectral analysis to obtain a quantized integrity value; comparing the quantized integrity value with a preset signal quality threshold; if the threshold is exceeded, adjusting the density distribution and recalculating the configuration to determine if the preset signal quality threshold has been reached.

5. The method for optimizing wire harness shielding and connection as described in claim 1, characterized in that, If the signal integrity data does not reach the preset signal quality threshold, the shielding structure is iteratively adjusted, including: collecting test data through signal integrity testing, determining that the preset threshold has not been reached, and obtaining the substandard frequency band indicators; comparing environmental factors with frequency band data to determine the interference impact assessment based on the substandard frequency band indicators and obtaining frequency band-specific optimization parameters; integrating vibration interference simulation based on the frequency band-specific optimization parameters, recalculating the shielding layer distribution fusion optimization parameters and vibration simulation data to obtain distribution adjustment values; comparing the distribution adjustment values ​​with the quality threshold to generate an updated design scheme, and determining that the signal integrity requirements are met.

6. The method for optimizing wire harness shielding and connection as described in claim 1, characterized in that, The multi-scenario simulation test of the shielding optimization scheme includes: simulating various complex environmental conditions for the updated design scheme using a pre-built multi-scenario simulation platform, obtaining response data of the harness under different environmental variables, and determining the initial anti-interference performance range; refining the recording of environmental variables with significant interference impact based on the initial anti-interference performance range, and obtaining detailed environmental interference distribution characteristics; adjusting and optimizing parameters to adapt to specific environmental variable control requirements by comparing and verifying the environmental interference distribution characteristics with existing shielding layer distribution parameters, and obtaining adjusted shielding layer configuration data; implementing a simulation test process for the adjusted shielding layer configuration data, collecting final data and comparing it with preset thresholds to determine the final shielding optimization scheme.

7. The method for optimizing wire harness shielding and connection as described in claim 1, characterized in that, The analysis of the damage trend of the connection terminals includes: collecting historical data on vibration damage and corrosion acceleration at the wire harness connection points, obtaining fatigue monitoring records of the terminal materials, and obtaining a preliminary damage index set; using the Arrhenius corrosion prediction model to analyze the damage trend of the connection terminals based on the preliminary damage index set, wherein the model inputs are the damage index set and time series data, and outputs predicted trend values ​​to obtain trend change curves; extracting the correlation features between corrosion acceleration and vibration damage from the trend change curves, obtaining feature values ​​by calculating the Pearson correlation coefficient, and obtaining a risk impact factor group; obtaining optimization adjustment parameters through simulated load testing based on the risk impact factor group, and obtaining the potential contact stability risk distribution.

8. The method for optimizing wire harness shielding and connection as described in claim 1, characterized in that, The integration of the optimized connection design data with the final shielding optimization scheme includes: performing data-layer fusion of the optimized connection design data and the final shielding optimization scheme to obtain integrated harness model data; simulating electromagnetic field distribution under preset broadband interference conditions for the harness model data to obtain an interference response curve; performing multi-factor durability testing by superimposing harsh environmental parameters on the interference response curve to determine a comprehensive tolerance index; implementing local modifications to the internal structural layout of the harness based on the comprehensive tolerance index to obtain a parameter correction set; and comparing the parameter correction set with a preset performance threshold to determine the final harness design parameters.

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