Browse Topic: Measurements

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J1979 Enhanced DBCJ1979DBC_202609To be published on 09/07/2026
The SAE J1979 Enhanced DBC file contains decoding rules for converting raw J1979 data to 'physical values' (Mph, %, etc.). This file lets you easily decode data from heavy duty vehicles (trucks, buses, tractors, etc.). This DBC file download includes: The SAE J1979 Enhanced DBC file with Includes 2,400+ Parameter Group Numbers (PGNs) and 16,000+ Suspect Parameter Numbers (SPNs), derived from the J1979 Digital Annex (DA) released in September 2026. One legal license (1 user, 1 PC) matching the DA license DECODE J1979: Convert J1979 data in wide range of software/API tools REVIEW FIRST: Use our CAN ID converter to check if your PGNs are covered CROWD INPUT: Benefit from free corrections based on large user base SAVE HOURS: Avoid manually constructing the DBC file from scratch Improved Accuracy & Reliability A fully standardized DBC file ensures precise signal decoding, eliminating errors and ensuring reliable data interpretation. Interoperability Seamlessly compatible with many different software stacks, enabling frictionless adoption and significantly expanding market reach. Partnership with Vector Informatik GmbH Works seamlessly with Vector’s free software (CANdb++), used by over 90% of the industry, with free download link provided on SAEI’s J1979DBC file landing page. What is a DBC file? A DBC file is a standardized method for storing the "rules" on how to interpret raw CAN bus data. It contains details on what 'signals' (e.g. RPM, Vehicle Speed, …) are contained within which 'messages' (i.e. CAN IDs). In the J1979 standard, messages are referred to as Parameter Group Numbers (PGN) and signals as Suspect Parameter Numbers (SPN). Further, a DBC file includes names, descriptions, positions, and lengths of the signals - as well as how to offset & scale them.
Amid the rapid development of the new energy vehicle industry, the vehicle frame, as the core load-bearing component of the entire vehicle, plays a direct role in the vehicle’s safety, lightweight design, and power performance through its design and performance. Although research on new energy vehicle frames has matured, issues related to the lightweighting of drive shaft-associated structures and the balance between weight reduction and strength/stiffness still require in-depth exploration. This study focuses on the chassis of new energy vehicles, utilizing Q295 low-alloy high-strength steel. Based on the vehicle’s dimensions and mass parameters, a simplified 3D model was constructed using SolidWorks. Static analysis under bending and torsion conditions, along with a 6th-order modal analysis, was conducted using ANSYS software. Based on the analysis results, optimizations were implemented at both structural and material levels: structurally, the central crossbeam was widened, holes were opened on the crossbeam’s vertical plane to reduce weight, and the longitudinal beam welding process was optimized; materially, Q295 steel was retained in high-stress zones, while aluminum alloy replaced it in low-stress zones. The optimized frame achieved a 15% reduction in torsional stress, a 16% decrease in bending stress, a 2% reduction in torsional deformation, and a 3% decrease in bending deformation. Total mass decreased by 12.7 kg, with both strength and stiffness meeting design requirements. This approach synergistically enhances frame lightweighting and performance, providing technical support for optimizing the overall performance of new energy vehicles.
Guo, LihongWang, YiyouYang, Zihao
This work introduces a novel parameter measurement model for an infrared detector. Firstly, the models for calculating the parameters of an infrared detector are studied and established, such as hysteresis, repeatability, and sensitivity. Then, experiments are implemented to validate and analyze the aforementioned parameters, demonstrating the accuracy and validity of the parameter computation model. This research has guiding significance for the accurate measurement of the index parameters of infrared detectors, and it is also helpful for the calibration method, error analysis and correction of infrared detectors.
Hu, ChangdeLi, YongQiangMiao, QiGao, SiliLiu, XiangyaoLi, Kunqi
As a high-precision transmission core component, the RV reducer’s performance depends on the time-varying stiffness of its core components. Building a time-varying stiffness model is essential for studying its dynamic characteristics. This paper addresses the lack of key factors in existing dynamic studies by creating a multi-factor coupled dynamic model. It analyzes the time-varying stiffness of the crankshaft bearing, involute gear, and cycloid gear-pin gear. The study also focuses on building a dynamic analysis model for the crankshaft bearing. By measuring changes in oil film thickness and initial assembly clearance caused by temperature rise, it explains how combined clearance affects bearing performance. To verify the model, a domestic RV reducer is modeled and assembled in SolidWorks. The simplified model is imported into ADAMS for simulation. Under set load and speed conditions, dynamic parameters like angular velocity and acceleration of core components are obtained. This provides a more scientific analysis method and data support for understanding the dynamic characteristics and improving the transmission performance of RV reducers.
Xuan, LiangTeng, ShaoweiHuang, RuizheWan, ZefuShao, MengqiYu, ZhishenWang, Ziyue
In this work, molecular dynamics simulations are applied to systematically examine the influence of varying temperatures (300 K, 500 K, and 700 K) on the Elevated-temperature compression behavior and micromechanical characteristics of polycrystalline Al-Mg-Si aluminum alloy. A nanopolycrystalline model was established to analyze the stress–strain response, dislocation evolution, and crystal structure changes occurring during the deformation process. The simulation results show that the yield strength and elastic modulus both decline as temperature increases, indicating a pronounced thermal softening effect. During the early stage of plastic deformation, dislocations mainly have their nucleation sites at grain boundaries and then propagate into the grain interiors, where they form interconnected networks along with stacking faults and twin structures. This work reveals the thermal deformation mechanisms of Al-Mg-Si aluminum alloy at the atomic scale and provides theoretical guidance for the optimization of its hot-working processes.
Sun, RuifengLiu, ShoukuiWang, RuiSun, XuemeiDing, ShuliMa, Xiaofei
Impact testing utilizing instrumented hammers and accelerometers is a widely adopted technique in dynamic testing. The mass loading effect of the accelerometer alters the dynamic response of the test structure, leading to deviations between the measured frequency response functions (FRFs) and their true values. Furthermore, the effects on the FRFs are contingent upon the positioning of the accelerometer, thereby causing the measured FRFs between two points to fail to meet the principle of reciprocity. This paper investigates the compensation method for the mass of a single accelerometer in impact testing. Compensation formulas for both origin–FRF and cross–FRF are derived using the frequency domain substructure decoupling method. Numerical simulations on a cantilever beam and experimental tests with milling tools validate the proposed methodology. The compensation formulas for FRFs presented in this paper are expected to enhance the measurement accuracy of FRFs in modal testing of small structures, particularly relevant for lightweight components in aerospace, aircraft, and transportation systems, where precise dynamic characterization is critical.
Tang, ZhenrongYao, Zhenqiang
During well testing and killing operations, tubing couplings with a larger diameter than the tubing body significantly increase the flow friction in the casing-tubing annulus, alter the rheological behavior of the kill fluid, thereby affecting operational accuracy and even leading to operational failure in severe cases. Most existing relevant studies focus on the impact of changes in flow area on flow, but ignore the effect of the coupling’s own structural configuration. Moreover, the research conclusions lack verification by downhole measured data, and there is an urgent need to further improve the analysis accuracy. Taking an ultra-deep well in the Xinjiang Oilfield as the engineering background, this paper conducts targeted research: first, a physical model of the flow field in the casing-tubing annulus passing through the tubing coupling is established, and a method for judging and determining the rheological properties of the kill fluid based on the fitting of the physical model and key parameters is proposed; on this basis, a numerical model including the coupling’s structural configuration is established and solved, and the friction calculation equation for the casing-tubing annulus passing through the tubing coupling is obtained through nonlinear fitting; finally, the calculation results of this equation are compared and verified with the measured data and numerical simulation results. The research results show that: under six working conditions, the flow characteristics of the kill fluid all conform to the characteristics of Bingham fluid, which is also consistent with the general flow regime of kill fluid flow; comparing the numerical analysis results of the target well in the Xinjiang Oilfield with the calculation results of the fitting equation, the maximum error, minimum error, and average error of friction analysis under the six working conditions are 14.46%, 0.39%, and 6.15% respectively; the total friction of the casing-tubing annulus in the entire well section calculated based on the theoretical equation is 12.085 MPa, and the relative error compared with the field measured 13 MPa is 7.57%, which meets the engineering accuracy requirements. The equation proposed in this study provides a universal equation for predicting the pressure drop of non-uniform flow in the wellbore, and also has an important reference value for predicting the wellbore pressure in drilling and oil-gas production operations.
Song, ZhitongJiang, WuMi, HongxueCao, YinpingDou, Yihua
This study aims to thoroughly explore the key influencing factors of e-cigarette atomization temperature to provide a scientific basis for e-cigarette product development and avoid the harmful substance release caused by excessively high atomization temperature. The fourth-generation e-cigarette was selected as the research object, and the atomization temperature was measured using a method based on the TCR (Temperature Coefficient of Resistance) to systematically investigate the effects of puff topographies (puff volume, puff interval, and puff duration), working parameters (output power and draw resistance), and solvent ratios on atomization temperature. The results show that solvent ratio, puff duration, power, puff interval (P<0.01), and puff volume (P<0.05) are significant influencing factors of atomization temperature. Puff duration and output power have positive correlations with atomization temperature, while puff volume, puff interval, and draw resistance have negative correlations. Regarding the solvent ratio, the atomization temperature generally increases with the increase of VG mass fraction in the e-liquid. This study proposes a novel method for measuring the atomization temperature and clarifies the influence of various factors on e-cigarette atomization temperature, analyzes the principles and degrees of influence, and provides theoretical support for optimizing e-cigarette design and reducing the health risks associated with excessively high atomization temperature, which is of great significance to the healthy development of the e-cigarette industry.
Xu, YupengZhou, MingzhuHao, DongLi, XiaohuiWang, JinpingZhou, DechengXing, Jun
Conventional measurement instruments such as scales, thermocouples, and laser-based technologies present challenges when used on lengthy and winding underground pipelines. These methods are often not feasible because of physical constraints, the challenge of light traveling in curves, and the need for large, energy-intensive sensors. Ultrasonic and microwave techniques both face challenges in making long-distance measurements because of rapid signal weakening and high energy requirements, which make them impractical for small pipes. This study introduces an original technique for Time-of-Flight (ToF) estimation using the Discrete Logarithmic Frequency (DLF) method to address these limitations. By analyzing the time–frequency correlations of signals transmitted through channels, the proposed technique enhances the precision and dependability of ToF measurements. By employing the DLF method, we are able to effectively gather and assess the signal’s performance as conduit lengths vary.
Chinni, Venkata Sai SandeepBalasubramanian, PrabakaranMamat, RizalmanYasin, Mohd
Penn Engineers have developed a novel design for solar-powered data centers that will orbit the Earth and could realistically scale to meet the growing demand for AI computing while reducing the environmental impact of data centers.
This study presents a refined design for pneumatic conveying pipelines, featuring a grooved structure at the bend aimed at reducing particle breakage during transportation. Using soybean particles as a focus, the research employs a gas-solid two-phase flow approach to explore how different groove depths and widths influence the breakage rate. We used CFD-DEM simulation techniques, combining fluid mechanics with discrete element modeling to achieve a more accurate representation of particle motion and collision forces during expressing. Based on these simulations, we identified the most effective combination of groove width and spacing. Experimental results showed that a groove width of 4.5 mm coupled with a 40 mm spacing could decrease impact forces on particles by approximately 5% to 10% at expressing speeds of 15 m/s and 20 m/s. Throughout all measured time intervals, the impact forces remained stable, with turbulence exerting minimal influence on the particle forces.
Luo, XinhaoYang, TianchengHuang, BoMao, GenwuDong, DeliangShi, HengLi, XiaoliangHe, Bo
Large-sized irregular castings are critical components extensively employed in large-scale equipment manufacturing. Due to their substantial dimensions and complex geometries, the assembly and docking processes between different components present significant challenges. To address the docking problem between large-scale irregular castings, this study proposes a casting docking method based on relative pose, along with a modeling approach for irregular castings, and accomplishes the docking process through the control of an industrial robot. Firstly, the current poses of feature points on the docking surfaces are measured. Based on these measurements, the relative pose transformation relationship between the center point of the docking surface and the robot’s Tool Center Point (TCP) is established, thereby constructing the docking model. This model calculates the relative deviation between the current pose and the theoretical pose. Subsequently, the robot motion is controlled according to this deviation to achieve precise docking. Finally, a simulation environment was built using KUKA. Sim Pro with Office Lite to simulate the docking process of large-sized irregular castings. The results demonstrate that the relative pose-based docking method effectively accomplishes the docking task. This study provides an effective solution for the docking of large-sized irregular castings.
Liu, HaoranJia, HailiWang, AiminXigang, FanPeidong, Su
The geometric error (GE) accounts for a significant factor affecting the machine tool’s machining accuracy, and in most cases, large GEs will result in a substantial deviation from the required shape of the machined workpiece. GEs are often observed in five-axis machine tools, and identifying and measuring these errors turns out to be challenging. In the present work, we proposed a novel GE identification approach based on simulations and tests conducted on a BC-type dual-rotary five-axis machine tool. Specifically, a machine tool volumetric error model (VEM), incorporating 41 GEs (the complete model), was constructed using the homogeneous coordinate transformation approach. Then, Sobol sensitivity analysis in conjunction with quasi-Monte Carlo estimation was introduced to the VEM to measure how much each GE contributed to the total volumetric error. The subsequent analysis identified 21 key geometric errors (KGEs). We also compared the simplified VEM and the complete model, and it was revealed that there was little difference between the two, which confirmed the effectiveness of our method. The present work is intended to provide a reference for simplifying VEMs, error element identification, and error compensation.
Zhang, JinlongShi, ZhaoyaoYang, Hongtao
Due to the inherent characteristics of large dimensions, complex curved surfaces, and densely distributed protrusions present in aerospace products, conventional offline programming and trajectory planning techniques for robots primarily prioritize the facilitation of uninterrupted grinding processes and the generation of points along trajectories on surfaces characterized by smoothness. However, these methods encounter challenges in identifying and proactively avoiding surface protrusions during the planning phase. The present paper puts forth a proposal for an automated robot trajectory planning method for grinding operations. This method is predicated on the integration of region partitioning and deformation correction. Specifically, this method first identifies protrusions based on curvature features and rule matching, followed by an analysis of the feasible workspace of a six-axis industrial robot equipped with an external axis. The product surface is discretized into multiple regional units according to the distribution characteristics of protrusions and the constraints of the feasible workspace. Subsequently, a parameter-optimized parallel sectioning method is employed to independently plan trajectories for each unit. The utilization of on-site measured point cloud data facilitates the analysis of contour deviations. In addition, grinding trajectories are dynamically corrected to meet high-precision process requirements. This approach effectively overcomes the challenge that trajectory planning for large-scale, complex-shaped products is easily affected by protrusions. According to the established methodology, the development of an offline programming software system for robotic automatic grinding was initiated. To this end, experiments were conducted on aircraft wall panels to plan and modify grinding trajectories using the proposed method. This process was undertaken to validate the effectiveness and engineering practicability of the proposed method.
Fan, ChanghaoWang, MingyangLv, RuiqiangZhou, Peng
Aiming at the measurement of buckling deformation defects of submarine pipelines in turbid waters, a precise measurement method for submarine pipeline deformation was proposed based on ultrasonic ranging technology. A unified underwater coordinate system for submarine pipelines and measurement sensors is established, and a three-dimensional model of the pipeline outer surface is constructed on this basis to provide a basis for calculating pipeline deformation elements. On the basis of underwater ultrasonic velocity correction, measurement accuracy control measures were proposed. Two types of ultrasonic measurement transducers and measurement systems were designed, and engineering applications were carried out to measure the deformation of submarine pipelines in the project. The measurement results indicate that the ultrasonic measurement system operates well under harsh sea conditions such as high turbidity, low visibility, and high flow velocity in the construction sea area, with high measurement accuracy. The three-dimensional model of the deformed pipeline is constructed accurately, and the deformation characteristics of the pipeline can be accurately calculated, meeting the requirements of engineering applications and providing effective data support for submarine pipeline maintenance.
Wang, KekuanHe, YazhangWang, HongZhang, TaoCheng, PeiliangSun, XinyanBai, Qian
The probe is an important component of the precision instrument. During the measurement process, the deformation of the leaf spring directly affects the accuracy of the displacement of the probe. There are many undetermined parameters for the leaf spring, and some parameters have a non-linear impact on the results. This paper proposes a firefly algorithm that combines penalty functions to solve the optimal solution of the objective function for multi parameter leaf springs. Through strategies such as normalizing mapping intervals, setting small populations between cells, and fine-tuning position update formulas, this algorithm quickly obtains the optimal parameters of the leaf spring, and compares it with the orthogonal experimental method to prove the feasibility of this method, providing a certain theoretical reference value for multi parameter solving.
Yu, JianghaoShi, ZhaoyaoSong, Huixu
This paper investigated the small deformation control of a large vertical vacuum vessel, a critical component in aerospace testing with stringent deformation limits under specific test conditions. Building on engineering experience and economic considerations, we designed oversized and multi-array external reinforcement rings tailored to the vessel’s spatial geometry to enhance its stiffness and stability. A novel integrated structural design was proposed, which mechanically couples the vacuum vessel with the concrete foundation via embedded components, specifically, by configuring optimized embedded parts at the vessel’s base and external reinforcement ring bottom, and then welding and binding these parts to the foundation’s embedded elements. This design significantly boosted the vertical vessel’s overall structural strength, rigidity, and stability. Ansys Workbench was used to simulate and analyze the vacuum vessel under different experimental conditions, and finite element simulations of the vessel under diverse experimental conditions validated that the integrated design achieves low stress and minimal deformation, compliant with test requirements. Post-installation deformation measurements further confirmed good agreement between experimental data and simulation results, verifying the model’s accuracy. The proposed fixed support structure addresses the limitations of traditional support systems for small-deformation applications and offers a new design paradigm for vertical vessel supports in high-precision engineering scenarios.
Bo, YangShizeng, LvXiao, HaoJie, Gong
In view of the key problems—low chip burn-in efficiency and high burn-in costs—caused by high R&D costs and a limited number of veneer stations in the traditional burn-in system used in the military aerospace field, this project has carried out a series of innovative research. Through systematic scheme optimization design and strict cost control measures, a new burn-in system with significant cost advantages and supporting multi-station parallel processing has been successfully developed for the aerospace field. The core technical breakthroughs of the system are mainly reflected in three aspects: first, through architectural reconstruction, the number of single incubator stations has been increased by leaps and bounds from the traditional 60 to 720; secondly, the use of intelligent monitoring technology can expand the scale of the workstation while using the display for process monitoring and data collection; Finally, the modular design concept is innovatively introduced, which greatly reduces the construction cost per workstation. Actual tests have verified that the processing efficiency of the AD1120 chip burn-in system has achieved a significant improvement of 1100%, which is equivalent to increasing the processing capacity of a single batch by 11 times. Up to now, the system has completed the 160-hour continuous burn-in test of 5,000 AD1120 chips, during which the system operation is stable and reliable, and there is no abnormality in the use of the test chip manufacturers. This breakthrough performance improvement not only significantly shortens the product development cycle but, more importantly, provides a practical technical solution for batch screening of high-reliability chips. Subsequent promotion and application can meet the mass production needs of a variety of chips in the aerospace industry, and provide a way to reduce costs and increase efficiency for the same type of unit.
Gu, ZuchengKang, XiaoJiang, Shang
To address the challenges of binocular vision ranging under complex environmental conditions—such as illumination variations, occlusion, and textureless regions, which result in unreliable and non-robust performance—this paper proposes a multi-source heterogeneous sensor fusion ranging method integrating 4D millimeter-wave radar with the YOLOv5-Monster framework. This method is capable of overcoming the issue of limited ranging accuracy in monocular or binocular vision algorithms under non-ideal imaging conditions. This study achieves high-precision spatial perception through the following specific pipeline: First, Zhang’s calibration method is used to obtain the intrinsic and extrinsic parameters of the binocular camera, and stereo rectification is performed on the raw images. Next, a lightweight YOLOv5 network is employed for object detection, while a high-performance Monster network is utilized to generate dense disparity maps, thereby accomplishing initial depth estimation. To mitigate the inherent depth estimation errors of vision-only systems, 3D point cloud data from a 4D millimeter-wave radar is further introduced. By applying a Kalman filter algorithm, the millimeter-wave radar point cloud and visual outputs are fused, achieving spatiotemporal synchronization and optimal state estimation across modalities and effectively correcting biases in visual ranging. Experimental results show that within the full range of 4 to 150 meters, the relative error of the proposed method remains below 5%. Specifically, the relative errors are 1.25% (absolute error: 0.05 m) at 4 meters, 1.40% at 5 meters, 2.99% at 75 meters, and 4.91% at 150 meters. Compared with the vision-only Monster-YOLOv5 baseline method, the relative error at 150 meters is reduced from 13.16% to 4.91%, representing an accuracy improvement of over 60%. Meanwhile, in terms of long-distance error control, the proposed method significantly outperforms traditional stereo matching approaches such as SGBM+YOLOv5 and BM+YOLOv5, reducing errors by more than 20 percentage points. These results verify that deep multi-modal fusion can enhance environmental adaptability and measurement reliability, providing a high-precision and highly robust solution for distance estimation in intelligent perception systems, which holds important theoretical and engineering significance.
Li, FugaiXie, YuwenSu, HaoLiu, DongleiWu, Qiong
Transporting large steel materials for mountain electric towers is challenging due to steep gradients, narrow roadways, and uneven terrain. To address these issues, this study designs an adaptive attitude adjustment mountain transport vehicle. This mountain transport vehicle has a compact structure, measuring 1.4 meters in length and 1.1 meters in width, which enhances its suitability for confined mountainous environments. This vehicle adopts a design scheme that combines hydraulic lateral adjustment, load-bearing platform follow-up adjustment and frame adaptive adjustment mechanisms. The transportation of tower materials, measuring 12 meters in length and 1.2 tons in weight, is accomplished by employing two vehicles working in coordination. The three-dimensional model of the entire vehicle is established by using SolidWorks software. The lateral stability of the mountain vehicle and the limit working conditions of its adjustment mechanism are analyzed through theoretical calculation. The dynamic simulation of the virtual prototype is carried out using Adams software, including the processes of lateral leveling, follow-up adjustment and frame adjustment. The results show that the leveling mechanism can achieve an adjustment range of more than ±25°. The results confirm the vehicle’s excellent stability and adaptability to mountainous conditions. This study provides a more effective and more reliable solution for the construction of mountain electric towers than traditional manual or animal-powered transportation methods.
Zhang, RuiKong, FanfangHe, YulingLv, JiahuiChen, ChanglongZhan, LulinLiang, Ke
The primary mirror support truss of large-aperture segmented telescopes, serving as a critical load-bearing component of the optical system, has its structural stability directly determining the optical imaging quality. This paper adopts a collaborative design method integrating topology optimization and size optimization to address issues, including excessive weight and unreasonable stiffness distribution in traditional support truss designs. First, based on the topology optimization theory of the Solid Isotropic Material with Penalization variable density method, topology optimization was performed on the initial truss structure using finite element simulation software, with the volume fraction as a constraint and the objective of maximizing structural stiffness to determine the optimal material distribution model. Subsequently, the truss structure was reconfigured based on the topology optimization results. Finally, the cross-sectional dimensions of the truss members were selected as optimization variables, and size optimization was performed using the NSGA-II multi-objective optimization algorithm with the objectives of minimizing structural weight and minimizing weighted compliance, while considering constraints such as stress and displacement. The results show that the optimized support truss achieves a 3.9% reduction in weight and a 35.47% decrease in elastic strain energy. This effectively meets the high-precision and lightweight design requirements for telescope support structures and provides a feasible technical solution for the design of large-aperture telescope support trusses.
Tan, DeliGuo, LiquanGao, DedongLiu, ChuanjieDai, XiaodongHuang, Lei
A two-dimensional (2-D) mixer has been widely used in the engineering field. The discrete element method (DEM) is capable of simulating and tracking collisions among particles inside the mixer. In this paper, the mixing process of spherical particles inside a 2-D mixer known as EYH150L is simulated by the DEM. The Lacey Index provides a quantitative measure of the blending efficacy achieved by a 2-D mixer. The DEM analysis indicated that the level of blending effectiveness among the particles in proximity to the rotating blades is significantly superior to that in regions devoid of blades. The rotational velocities of particles in blade-free zones are about 40% of those near the rotating blades, which serves as a key factor accounting for the slower increase in mixing efficiency observed in these regions. To address this disparity and enhance overall mixing performance, a mirrored rotating blade was incorporated, positioned to the left of the baseline revolving cylinder, thereby optimizing the structural configuration of the 2-D mixer. The verification tests indicated that the modification increases the mixing efficiency of the mixer at its left side, and enhances the blending uniformity, ensuring the four particle types are mixed equitably.
Fang, ZiqiangLiu, YongChen, Yafeng
This study presents a comparative analysis of the braking performance of a heavy commercial vehicle under in-gear and out-of- gear conditions, combining experimental tests conducted at 60 km/h with high-fidelity computational simulation. The numerical model incorporates real engine torque, power, and motoring/braking curves, full brake system parameters, dynamic load transfer, tire–road friction characteristics, and ABS actuation. Simulation results were validated against experimental MFDD and stopping distance measurements. The simulation demonstrated a high correlation with the experimental MFDD values (5.3 vs. 5.36 m/s2 in the in-gear condition and 5.6 vs. 5.37 m/s2 in the out-of-gear condition), confirming the robustness of the model. Differences in stopping distance were attributed primarily to the real-world behavior of the ABS and to variability in the road surface friction coefficient. The study concludes that braking with the vehicle in gear provides improved longitudinal stability due to the resistive contribution of engine drag torque, which also reduces the thermal load on the service brakes. Overall, the results reinforce the essential role of simulation as a development, optimization, and certification tool for brake systems.
Junior, Getulio SoaresCanale, Antônio Carlosde Oliveira, Sergio Henrique FidelisPizzi, Rafael Fortuna
This SAE Aerospace Recommended Practice (ARP) defines the minimum across hexagon corner dimensions for fluid tube fittings and nuts. The ARP covers commonly specified inch and millimeter hexagon sizes.
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
Tubing Ultimate burst strength Full scale test
Cheng, WenjiaYang, HongbinGe, YuanZhong, ChongdiMeng, LingkunJi, BingyinShi, Jiaoqi
To address the detection and monitoring needs of fatigue damage in ferromagnetic materials, this paper proposes a nondestructive testing method based on the evolution of magnetic hysteresis characteristics. By constructing a hysteresis loop measurement system, the variation patterns of coercivity (Hc) in Q235 steel specimens under cyclic loading were investigated, revealing three-phase characteristics of fatigue damage: the initial linear growth phase (N ≤ 8,000), the rapid rise phase (8,000 < N ≤ 12,000), and the stable oscillation phase (N > 12,000). Experimental results demonstrate that the relationship between coercivity and damage degree (D) can effectively characterize the processes of crack initiation, propagation, and instability, with significant inflection points observed at D = 0.6 and D = 0.8. The quantitative model based on coercivity provides a novel method for early warning and condition assessment of fatigue damage, offering advantages such as non-contact operation and high sensitivity. This study provides theoretical foundations and technical support for the health monitoring of engineering structures.
Chen, LiDing, Keqin
Spacecraft with chemical propellant engines, especially spacecraft for exploring extraterrestrial objects, need to carry out plume tests on the ground in order to determine the influence of engine plumes on spacecraft. An important purpose of the plume test is to accurately measure the pressure field in key parts of the spacecraft. In this paper, according to the pressure measurement requirements of the spacecraft plume test, the design of a pressure measurement system is carried out, which mainly includes a pressure measurement sensor, a pressure difference measurement sensor, a pipeline, a cable, a measuring instrument, a data acquisition instrument, upper measurement software, and so on. The designed pressure measurement system was successfully applied to the plume impact test of Chang'e VII, which provided important technical support for the development of the spacecraft.
Wu, YueGuo, QinliangWu, DongliangLiu, XiaoningTao, DongxingLin, BoyingXie, ZhengWei, XiNiu, Tong
This paper investigates the tracking of highly maneuverable targets during flight and the corresponding satellite scheduling problem in a space-based observation system. Based on dual-satellite measurements, a nonlinear observation equation was formulated. The J2 perturbation model and the current statistical model were utilized within an Interacting Multiple Model filtering framework to achieve adaptive estimation of the target states of the boost-glide vehicles. Building upon this framework, a greedy satellite scheduling algorithm based on IMM model probabilities is proposed. This method dynamically selects the optimal measurement set within a given prediction window to maximize observation performance. The proposed strategy is compared against rolling-horizon scheduling and fast-slow timescale scheduling approaches. Simulation results demonstrate that the proposed method effectively adjusts model weights in response to target maneuvers, enhancing adaptability during highly maneuverable phases. Meanwhile, it reduces the number of satellite switches while maintaining estimation accuracy, significantly improving scheduling efficiency and tracking continuity.
Deng, SiruiLiu, ChengzheWang, Yandong
Pollution in the oxygen system of civil aircraft may lead to fire accidents, and maintaining the cleanliness of oxygen equipment is the most effective measure to reduce the risk of fire. This paper introduces the cleanliness requirements, cleaning methods, and procedures of oxygen equipment, and combines the cleanliness level requirements of oxygen equipment for a certain type of civil aircraft. By detecting the total weight of Non-Volatile Residue and the size and quantity of particles on the surface of the parts, it verifies whether the specific cleaning process can meet the cleanliness level required by the design. In addition, the possible sources of pollutants are analyzed based on the first unqualified verification results, and targeted improvement directions for the process are provided. After re-performing the cleanliness verification test, the results passed successfully, indicating that the process improvement is effective and has passed the airworthiness certification of the reviewer.
Huang, Jingqi
To ensure the successful implementation of the separation, evacuation, and return processes of manned spacecraft after long-term docking at the space station, regular on-orbit health assessments must be conducted. Based on this requirement, a technical method for evaluation through autonomous on-orbit testing is proposed. First, the docking status and characteristics of the manned spacecraft’s systems, such as information management, crew environmental control, thermal control, power management, docking function, attitude, and orbit control function, are described. Then, the functional requirements for the separation, evacuation, and return of the manned spacecraft, such as the relative measurement, the relay communication, TT&C and data transmission, image and voice, instrument display and alarm, and the attitude measurement, are analyzed. Subsequently, the on-orbit testing system, test items, test procedures, and test methods for health assessment are detailed. It also provides the design of TT&C support, the design of energy support, and the main principle explanation for autonomous on-orbit testing of the system.
Cheng, WeiNan, HongtaoTian, YeZhao, Zheng
The development of remote tower systems in aviation and the resurgence of multi-display interfaces and virtual environments have dramatically influenced ATC, increasing both controllers’ visual demands and their ergonomic needs. This study uses the Visual Ergonomics to study the impact of screen luminance level, along with color temperature, on trainees’ visual performance, fatigue, and physical discomfort in the control rooms of the Remote Tower. By combining a simulated remote control system with spectrometer measurements, PVT alertness tests, VMT (Visual Memory Test) measurements, and subjective evaluations, COST B21 can build up a multi-dimensional ergonomic assessment framework. Eight levels of display luminance (and color temperature) were tested, including two illuminance levels (300 lx and 400 lx) and four color temperature ranges (6000 K–9000 K). Using the Analytic Hierarchy Process (AHP), these parameters were assigned weights to derive a Visual Ergonomics (VE) scoring model, and the ideal visual performance was observed at 400 lx illuminance and 8000 K CCT. The results clearly illustrate the significant impact of display parameters on operational performance in remote tower systems and provide both practical data and a theoretical basis for the human factors design and fatigue reduction research on RTSs.
Zhong, LinfengHu, RuohuiLuo, PeilinZuo, QinghaiZhong, QingweiAi, Yi
This paper proposes a multi-source dynamic error compensation algorithm for the transfer alignment of airborne optoelectronic payloads. This method addresses performance limitations of micro-inertial navigation systems (micro-INS) in complex dynamic environments, specifically those arising from accumulated device noise and the inability to perform static alignment due to installation errors. The algorithm’s core is the Extended Kalman Filter (EKF) technology. By constructing a “velocity + attitude” matching model between the UAV’s master inertial navigation system (MINS) and the optoelectronic payload’s slave inertial navigation system (SINS), it leverages high-precision MINS navigation information to correct SINS errors. Utilizing a 21-dimensional state space equation and measurement equation, the algorithm achieves real-time estimation and compensation of various errors, including attitude misalignment angles, sensor biases, installation errors, and flexure deformation. Simulation results demonstrate significant alignment accuracy improvement. Post-lever arm effect compensation, velocity errors are stably controlled within 0.01 m/s. Concurrently, flexure deformation angle compensation substantially reduces misalignment angle fluctuations across all directions, enhancing system stability and maintaining low misalignment angles. These findings validate the proposed error compensation strategy’s effectiveness.
Zhang, LuLi, MaoWang, ShiyongLei, Chao
Analysis of cabin depressurization is key to ensuring civil aircraft airworthiness safety. In this study, we use a comprehensive approach to analyze depressurization scenes under regulations such as CCAR 25.841. For cases with and without cabin altitude warnings, we calculated critical leakage areas using an orifice flow model and iterative numerical methods. This combines inputs like emergency descent envelopes, air supply rates, and cabin parameters. In our analysis, we evaluate system failure impact and structural breaches on cabin pressure dynamics. For cases where the critical leakage area failed to meet the limits, we use an equivalent safety analysis based on the Depressurization Exposure Index (DEI). This combines pressure and exposure duration to measure physiological risks. We validated this approach through Simulink simulations and case studies, and found that it supports airworthiness verification, emergency descent optimization, and structural design improvements. This method provides a robust framework for enhancing civil aircraft depressurization safety.
Zheng, Bian
To solve a problem that ignition anomaly can’t be detected in time, based on the thermal equilibrium equation, the space heat flow, heater heating, propellant combustion, and thermal radiation to cryogenic space are considered to build an accurate ignition temperature method for the 10 N thruster by using on-orbit true temperature. Further, considering the error of measuring the thermistor, an envelope model for the 10 N thruster ignition temperature is established. Based on the above, a detection method for the 10 N thruster ignition anomaly of on-orbit satellites is proposed. The accuracy of the method is relatively high, and the absolute error is less than 3 degrees Celsius. An anomaly can be quickly detected when the 10N thruster ignition temperature deviates from the normal trend by 3–5 degrees celsius. The method is applied to a DFH-3 satellite, and the maximum difference of 10 N thruster ignition temperature between the theoretical values calculated by the proposed method and the measured values is only 2.72 degrees celsius. It has been proven that the prediction accuracy of the proposed method is high. It plays an important role in discovering the 10N thruster ignition anomaly in time and ensuring the success of satellite orbit or attitude control.
Li, LilingTian, HuadongWei, YuboFei, DiXing, Chao
To enhance the rescue efficiency of expressway emergencies and reduce the impact on network operation, this study developed an optimization model for the strategic placement of emergency rescue stations. Firstly, a node importance assessment method is designed to measure the importance of each node in the expressway network by considering both local and global impacts; secondly, an emergency rescue station selection model is constructed based on the node importance to achieve the highest coverage satisfaction, the highest rescue efficiency and the lowest construction cost. Taking the expressway network in Shaanxi Province as an example, a particle swarm algorithm based on non-dominated sorting (NSPSO) is designed to solve the problem. The results demonstrate that, with the same number of rescue stations, the model of Site Selection of Emergency Rescue Stations considering node importance achieves shorter average rescue time and higher coverage satisfaction under comparable conditions.
Chen, JingliLin, ShanXu, HongkeCao, JiabaoYang, FeiLuo, Mi
The magnetic field modeling methodology for ships based on magnetic dipole arrays demonstrates heightened sensitivity to input data. When addressing overdetermined systems characterized by numerous variables and constrained measurement points, the coefficient matrix frequently develops pathological ill-conditioning, leading to solution divergence and compromised result accuracy. This research reformulates the ship magnetic field inversion challenge as a non-convex quadratic programming problem, employing the Successive Convex Approximation (SCA) algorithm as the computational solver. Rigorous comparative validation was performed against conventional stepwise regression algorithms and experimental datasets acquired from scaled ship model measurements. Results substantiate that while the modeling precision of the SCA algorithm remains comparable to that achieved by stepwise regression methods, SCA exhibits demonstrably superior solution stability. This enhanced robustness positions SCA as a more reliable computational framework for critical naval applications, particularly in high-fidelity ship magnetic signature modeling and rapid detection/localization of magnetic targets in marine environments.
Chen, HaoPan, Xun
The features of airport clusters have a big impact on regional air transport. But problems within these clusters also affect airline operations. This study uses the Data Envelopment Analysis (DEA) model. It selects 16 airlines of different sizes as samples. It also identifies relevant input and output indicators to measure operational efficiency. The results show that the efficiency of large and medium-sized airlines generally went up. Small airlines have shown a slow but steady improvement in efficiency, with significant volatility due to cost and slot constraints. So, the study analyzes pure technical efficiency, scale efficiency, and comprehensive efficiency. It finds out the changing patterns of operational efficiency among airlines of different sizes and the reasons behind them.
Hu, KexinHuang, Tao
This paper presents a monocular vision-based system for high-precision missile pose measurement using ArUco markers and Perspective-n-Point (PnP) algorithms. By deploying 6 × 6 ArUco markers on a cylindrical missile mock-up, the system establishes 3D-2D correspondences between structured-light-scanned models and camera images to solve the PnP problem. The proposed approach integrates optimized ArUco marker recognition — leveraging adaptive thresholding, contour simplification, and grid-based validation — with the Efficient PnP (EPnP) algorithm to achieve real-time pose estimation. Experimental validation demonstrates angular accuracy of ± 0.3° in roll/pitch/yaw and positional accuracy of ± 2 mm within a 2 m range under controlled conditions. The system exhibits robustness against partial occlusions and motion blur, with degraded performance (± 1.2°, ± 5 mm) in extreme scenarios. Key innovations include a streamlined marker detection pipeline and adaptive pose refinement using Levenberg-Marquardt optimization. This work provides a cost-effective, non-contact solution for flight tests, with potential applications in weapon separation testing.
Wang, RuiyangZhang, Chaofan
Nowadays, the majority of intelligent fault diagnosis approaches are still centered on individual faulty components, while only a limited number of models are capable of performing integrated diagnosis for rotating systems that consist of shafts, bearings, and gears. Under variable-speed operating conditions, the large scale of vibration data further complicates the process of effective feature extraction. To improve these challenges, this study develops a comprehensive diagnostic framework for rotating components, termed WGAN-SAFC. The proposed architecture integrates a Wasserstein Generative Adversarial Network (WGAN) with a hybrid structure of stacked autoencoders and sparse filtering (SAFC). SAFC integrates the feature-learning capability of SAE and the sparsity-driven representation of SF, while incorporating adversarial data generation to address sample imbalance and enhance fault diagnosis performance. Experimental verification on collected vibration datasets demonstrates that WGAN-SAFC achieves superior diagnostic accuracy and robustness compared with existing methods.
Li, ShunmingFeng, Mengqi
As high-speed train technology advances, the demands on braking system performance have intensified. Known for their efficiency, reliability, and eco-friendliness, Linear Eddy Current Brakes (LECB) have become a focal point in the research and development of high-speed train braking systems. This paper presents an innovative Orthogonal Excitation Eddy Current Brake (OEECB), which enhances the braking force without modifying the overall dimensions of the conventional LECB. By adding a set of longitudinal excitation coils parallel to the rail surface, the OEECB creates an orthogonal excitation structure that augments the braking force. Initially, this paper outlines the design concept of the OEECB and then analyzes its working principle based on electromagnetic field theory. Subsequently, a finite element solver is employed to numerically model the electromagnetic characteristics of the OEECB. Finally, by comparing the performance differences between the conventional LECB and OEECB, the superiority of the OEECB in enhancing braking performance is demonstrated. The results indicate that under the same excitation current conditions, the OEECB increases the braking force by over 20 % while maintaining a controllable increase in attractive force.
Huang, LiuwenZuo, JianyongZhang, Yu
The gearbox is a key component of the mechanical transmission system, and its fault diagnosis is essential to the reliability of the equipment. However, obtaining fault samples under actual working conditions for gearbox fault diagnosis is challenging. In this paper, the rigid-flexible coupling dynamic simulation model of the gearbox is established, and the co-simulation of gear normal, crack, and breakage is carried out in the ADAMS and MATLAB environments. The comparison between the simulated and measured signals shows that the simulation method can accurately reflect the key characteristics, such as rotation frequency and meshing frequency, and verify its reliability and accuracy. The research results can provide effective data support for gearbox fault diagnosis and improve the operational safety of mechanical systems.
Li, DongxiaoZhang, QianqiZhang, ZhongzhengLi, Yongbo
The aim of this work is to develop a modular, real-time-capable digital twin of an electric powertrain based on machine learning (ML)-based model structures and a systematic, component-oriented architecture with a focus on efficiency estimation in test bench environments. The further goal here is to enable virtual testing, which can be used for frontloading and thus both prevent errors and increase the speed of product development. Based on a comprehensive set of measured and derived test bench data, a multi-stage procedure is implemented that integrates data acquisition, physically informed feature selection, modeling at the component and subsystem level, and hybrid coupling strategies. The digital twin captures inverter, electric machine, and mechanical transmission stages and generates consistent predictions of key variables such as torque, speed, power factors, and subsystem as well as overall drivetrain efficiency. The methodology enables a systematic comparison of black box, dark grey box, grey box, and bright grey box architectures with respect to prediction accuracy, information content, and real-time capability. The methodology provided uses new model structures that explicitly integrate physical dependencies while also using ML models to map nonlinear effects. The hybrid architectures presented have been shown to significantly reduce the measurement effort while achieving nearly identical model quality and surpassing purely physics-based models in terms of accuracy, robustness, and real-time capability. For the final bright grey-box architecture, average relative efficiency errors below 1 % are achieved while maintaining real-time execution rates. The study shows that bright grey box-models in particular offer a best-case compromise between the requirements of information content, error quality, and synchronization rate, thus representing a methodological advance over conventional digital twins, which are often created at the component level. The shown methodology provides an implementable framework for digital twins of electric powertrains in industrial test environments.
Kopp, LennartProksch, DanielOckert, NielsKarthaus, CarstenKley, Markus
This study describes a methodology for synthesizing representative driving cycles for light commercial vehicles. The focus is on taking the usage profiles of these vehicles into account in the driving cycle synthesis. In this methodology, representative routes are simulated using the example of light commercial vehicles in the craft sector. The results of these simulations are representative speed distributions and representative altitude variations. These results are then used as target values for the actual driving cycle synthesis. Furthermore, measurement runs are carried out with a light commercial vehicle to create a database of real-world driving data. The measurement runs include different urban, rural, and motorway sections and cover a total distance of approximately 510 km. Routes with flatter and more challenging altitude profiles are driven. During the measurement runs, the speed signal and the altitude signal are measured. These signals are then processed and cut into short segments, each consisting of a speed and altitude profile. This is followed by the actual driving cycle synthesis, in which those segments with suitable altitude variations are assembled according to the representative speed distributions. This paper examines three different usage profiles of light commercial vehicles in three different cities in Germany. These three cities are Ulm (large city), Stuttgart (metropolitan region), and Munderkingen (small town in rural region). The results of these three analyses show considerable differences both in the calculated speed distributions and in the calculated altitude variations. For example, the usage profile in the rural region of Munderkingen shows significantly higher rural proportions than the usage profile in the Stuttgart metropolitan region. Furthermore, the analysis in Stuttgart shows a much higher altitude variation than the usage profile in Ulm. These differences highlight the need to take vehicle usage profiles into account in the driving cycle synthesis.
Heilmann, OliverGrabow, AndreasCortès, SvenSchlick, MichaelStoll, TobiasKulzer, André Casal
Accurate tire models are a key enabler for vehicle dynamics simulation, control design, and lap time optimization, particularly in the context of Formula Student race cars, where vehicle setups and tire characteristics differ significantly from production vehicles. State-of-the-art tire models, such as Pacejka’s Magic Formula, generally provide high prediction accuracy. However, their predefined functional structure and large number of coupled parameters are designed for broad applicability across many tire types rather than for specific racing tires. This often results in limited interpretability, nontrivial parameter identification, and unnecessary model complexity for specialized applications such as Formula Student. This paper presents a data-driven approach for deriving compact and physically interpretable tire force models using symbolic regression. The proposed method employs an intelligent tree search to systematically explore the space of mathematical expressions and identify models that optimally balance prediction accuracy and structural simplicity. In contrast to black-box machine learning approaches, the resulting models consist of explicit mathematical expressions that enable physical interpretation and efficient evaluation. The methodology is applied to experimental tire test bench data, focusing on the lateral force – slip angle relationship at constant vertical load. In a first step, the symbolic regression algorithm is utilized to derive a set of candidate mathematical expressions. These models are subsequently benchmarked against 200 independent data sets comprising various tire types and vertical loads. The evaluation reveals that the identified models approximate the measured tire behavior with accuracy comparable to, and in many cases exceeding, the Magic Formula, while exhibiting lower model complexity. The results demonstrate that symbolic regression can uncover alternative tire models that better represent the characteristics of Formula Student racing tires than conventional approaches. Owing to their compact structure and physical consistency, the derived models are particularly well suited for real-time vehicle simulations, parameter studies, and control-oriented applications in Formula Student vehicle development.
Anselment, MarcelBorowski, JulianRudolph, Stephan
With the continued expansion of electric mobility, liquid-cooled thermal management systems have become indispensable for ensuring the performance, durability, and safety of automotive battery packs. This work presents a novel cooling-plate design that integrates offset strip-fin turbulators to enhance convective heat transfer between lithium-ion cells and the circulating coolant. A comprehensive multi-region CFD model of the full battery pack is developed, incorporating an implicit lumped-parameter representation of cell heat generation. The numerical predictions are validated against dedicated experimental measurements available in the literature. Subsequently, a parametric study is conducted in which the number of hydraulic sub-modules and the inlet/outlet configurations are systematically varied to generate all feasible design permutations. The resulting configurations are compared to assess thermal performance and to quantify the benefits—as well as the potential penalties—introduced by the turbulators relative to the experimentally validated baseline.
Montenegro, GianlucaOnorati, AngeloDella Torre, AugustoTariq, Muhammad HasnainBonetti, Elisa
Current lithium-ion batteries should generally only be charged above 0 °C, as charging below this temperature can promote lithium plating and irreversible degradation. However, conventional pack-level heating elements increase system mass and design complexity. In addition, heat is transferred from outside into the cell, causing the temperature inside the cell to rise slowly. This study evaluates internal Joule heating of cylindrical Li-ion cells using a zero-mean square-wave current excitation and quantifies the associated aging impact. LG INR21700-M50L cells were tested at 0 °C, −10 °C, and −20 °C with three excitation frequencies (50 Hz, 1 Hz, 10 mHz) at 5 A amplitude. Each cycle consisted of 30 min heating followed by 60 min cooling; reference capacity-based state of health (SOH) was assessed every 50 cycles up to 400 cycles. A maximum surface temperature rise of 14.3 K was achieved, with larger temperature rise at lower ambient temperature and lower excitation frequency. Capacity fade remained below approximately 1% for most conditions; however, at −20 °C and 10 mHz a pronounced SOH decrease to 87% was observed, indicating a critical operating regime. The results provide practical guidance for pulse-heating parameter selection and highlight the need for safeguards and further diagnostics in extreme low-frequency excitation at very low temperatures. This heating approach is particularly suitable for simpler battery-electric applications without thermal management, such as e-bikes or power tools. However, it may also be relevant for applications with existing thermal management systems, as it simplifies battery pack design.
Raiber, StefanAllmendinger, FrankDegler, DavidParschau, Anke
This paper presents the development of a speed controller for e-bikes, designed as part of an energy-adaptive assistance system. The controller provides riders with appropriate support along planned routes, based on the available battery capacity. The control concept is intended for integration into existing commercial e-bikes without requiring extensive modifications to the drive system. Therefore, the rider remains part of the control loop, adjusting the support mode according to instructions from the controller. The speed controller is implemented as a rule-based state machine, enabling comprehensible design and parameterization. Since the rider must manually switch between support modes while riding, the control logic incorporates hysteresis and dead times to ensure stability, prevent oscillations, and avoid frequent mode switching. The user interface is a smartphone application that issues visual and audio instructions for switching support modes. An initial, system-independent version that relied on GPS-based speed measurement was found to be insufficiently accurate for the control task. Furthermore, it was found that detection of the pedaling state was essential for proper operation. To address these issues, a Bluetooth-based hardware adapter was developed to access relevant signals from the e-bike’s CAN bus communication system. These include pedal power, cadence and speed, which are made accessible through reverse engineering of the CAN bus. The proposed concept is evaluated in a chassis dynamometer study with 13 participants on two test profiles: a synthetic gradient profile for assessing control stability and a realistic elevation profile for dynamic evaluation. Additional measurements taken with one of the test riders at different speeds demonstrate the system’s reliability and its potential to improve the energy efficiency. The results show that, with approximately the same power brought in by the rider, only 27% more electrical energy is required to increase the average speed by 45%.
Rauch, YannickSimmann, GabrielSchneider, ManuelGoss, ChristianKriesten, Reiner
Traditional industrial robotics has been built on traditional premises: define the task precisely, program the motion, and repeat it with minimal variation. This model has delivered reliability, speed, and scale across multiple application domains.
Acoustic user interfaces and audio experiences are among the leading comfort factors in new vehicle interior designs. OEMs are more and more focusing on loudspeaker design and positioning, to provide the most immersive experience to the customers. The industrial target is to be able to predict the performance of an audio system in early design phases. This paper presents an integrated vibro-acoustic methodology enabling early-stage prediction of loudspeaker performance in real vehicle conditions. The approach combines electromechanical characterization, a hybrid loudspeaker calibrated model valid across the audible range and coupled FEM/BEM/SEA simulations to capture the loudspeaker response in the vehicle’s cabin considering door-installation effects and cabin acoustics. The method is validated experimentally on a rear-door loudspeaker installed in a production vehicle, showing strong correlation with measured SPL. A final application case demonstrates its capability to assess the impact of alternative speaker mounting positions during the design phase.
Zerrad, MehdiErrico, FabrizioMordillat, Philippe
For analysing flow and acoustic induced structural vibration, a fully run time coupled framework combining a hybrid CFD-CAA approach with a modal response simulation was validated and presented at the ISVNH 2022 (SAE Technical Paper 2022-01-0938). In this paper i We apply this CFD–CAA–modal coupling method to a series-representative bonnet geometry and demonstrate its capability to capture flow and aeroacoustically driven vibration with two-way coupling. ii We analyse the modal properties of the bonnet and show that confined air volumes beneath the bonnet can introduce significant fluid loading effects, which are already embedded in experimentally validated FE modal models and must therefore be treated carefully in two-way coupled simulations. iii We validate the fully coupled aeroelastic simulation against wind-tunnel measurements with undisturbed inflow, show close agreement with the measured vibration response and analyse that the dominant excitation is in this case from below the bonnet due to acoustic pressure fluctuations.
Schwertfirm, FlorianOcker, JoergHartmann, Michael
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