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Finite element (FE) based simulations for fully trimmed bodies are a key tool in the automotive industry to predict and understand the Noise, Vibration and Harshness (NVH) behavior of a complete car. While structural and acoustic transfer functions are nowadays straight-forward to obtain from such models, the comprehensive understanding of the intrinsic behavior of the complete car is more complex to achieve, in particular when it comes to the contribution of each sub-part to the global response. This paper proposes a complete target cascading process, which first assesses which sub-part of the car is the most contributing to the interior noise, then decomposes the total structure-borne acoustic transfer function into several intermediate transfer functions, allowing to better understand the effect of local design changes.

During the vehicle lifecycle, customers are able to directly perceive the outer panel stiffness of vehicles in various environmental conditions. The outer panel stiffness is an important factor for customers to perceive the robustness of the vehicle. In the real test of outer panel stiffness after prototype production, evaluators manually press the outer panel in advance to identify vulnerable areas to be tested and evaluate the performance only in those area. However, when developing the outer panel stiffness performance using FEA (Finite Element Analysis) before releasing the drawing, it is not possible to filter out these areas, so the entire outer panel must be evaluated. This requires a significant amount of computing resources and manpower. In this study, an approach utilizing artificial intelligence was proposed to streamline the outer panel stiffness analysis and improve development reliability.

In the early stages of vehicle development, it is critical to establish performance goals for the major systems. The fundamental modes of body and chassis frames are typically assessed using FE models that are discretized using shell elements. However, the use of the shell-based FE method is problematic in terms of fast analysis and quick decision-making, especially during the concept phase of a vehicle design because it takes much time and effort for detailed modeling. To overcome this weakness, a one-dimensional (1D) method based on beam elements has been extensively studied over several decades, but it was not successful because of low accuracy for thin-walled beam structures. This investigation proposes a 1D method based on thin-walled beam theory with comparable accuracy to shell models. Most body pillars and chassis frame members are composed of thin-walled beam structures because of the high stiffness-to-mass ratio of thin-walled cross sections.

As data science technologies are being widely applied on various industries, the importance of data itself increased. A typical manufacturer company has a vast data set of products as 2D&3D drawing formats, but a common problem was that building a database from the 2D&3D drawings costs much, and it is hard to update the database after it once built. Also, it is high-cost job when the new factor researched and necessary to investigate the new factors on previously fixed or uploaded drawings. As new products are developed with time, these problems are getting more difficult. In this paper, an automated database building method using CATIA introduced and future probabilities are suggested. An aluminum wheel part was used as an example. An automated logic used CATIA V5’s VBA functions and was handled by python programming language.

In electric-powertrains, noise and vibration can be generated by components such as gears and motors. Often a noise phenomenon known as rumble or droning noise can occur due to low shaft order excitation at the spline. In this study, we identified the excitation source for spline induced rumble noise and developed a novel analysis method. First, a detailed spline model, believed to be the key factor for rumble noise, has been developed and verified by comparison with Finite Element Method(FEM) analysis. In order to identify an excitation source, a typical electric-powertrain assembly model including the developed spline model was constructed and simulated. Results according to changes of key factors including spline pitch errors and shaft alignment errors were analyzed. Spline radial force has been identified as an excitation source of spline induced rumble noise. This was verified through comparison with the forced vibration analysis result and time domain analysis result.

Generally, the HVAC system of a vehicle is composed of Blower unit assembly and Heater unit assembly, and is located on the driver’s side of the dash panel. However, electric vehicles have far fewer parts than conventional internal combustion engine vehicles, so electric vehicles have large space in the engine room. This allows HVAC, which occupies large volume in the interior side, to be pushed in the direction of the engine room altogether, or by placing a part inside the engine room to make a slim cockpit and expand the interior space. However, this new structure, called the Split HVAC System, is mounted through the dash, allowing noise to pass through relatively easily. Since this adversely affects the NVH of an electric vehicle, it needs to be developed in terms of noise transmission. Therefore, in this paper, a study was conducted to predict the sound transmission loss of Split HVAC through an analytical method.

In this paper, an application process is studied at which the insertion loss (IL) test data of sound insulating parts or noise control treatments are utilized for the sound transmission loss (STL) simulation of the trimmed dash structure. The considered sound barrier assemblies were composed of a felt layer, a mass layer, and a decoupler layer. Flat samples of sound barrier assemblies with several different thicknesses were prepared, and ILs of them were measured by using a sound transmission loss facility. Flat samples were assumed to have mass-spring-mass resonance frequencies. The mass was set as the area mass of the sound barrier layer of the felt layer and the mass layer. The spring constant of the decoupler layer was assumed as the multiplication of that of an air spring and a spring correction factor.

NVH analysis based on numerical simulations before actual test vehicle is available becomes common process in the automotive industry. Furthermore, the latest work scope is extending even to conceptual study in the very early design stage, beyond traditional numerical simulations simply using 3-D CAD data. In case when reasonable information is provided at this very early vehicle development stage, a better decision on the design concept would be possible, and subsequent design process can be carried out in more efficient manner. The core of this trend is that it allows us to predict vehicle performance at the conceptual design stage without 3-D CAD data, and then, with this prediction, to suggest meaningful design directions for next stage. From this point of view, FRF-Based Substructuring (FBS) methodology has potential to be used as an appropriate tool for this purpose.

This study presents a design methodology to predict the crash behavior of mid-size sedan with a simplified crash model. Without detailed conventional finite element, the simplified crash model can be adopted in the early stage of the vehicle design. Designing vehicle structure to satisfy crash performance target is highly complex problem in the early design stage, because of the nonlinear mechanical behavior, high number of degrees-of-freedom, lack of information and boundary conditions changing over the following development process. In this study, the front structure of the vehicle is divided into load-carrying members and the rigid element through the analysis of load-carrying mechanism, and its physical property (force-displacement relation) is parameterized as the property of the non-linear discrete beam element of the LS-DYNA. The effectiveness of the proposed research is shown by the example of the mid-size sedan.

Body-in-white plays a key role in protecting passengers in the event of collision between vehicles, and also endures external forces during cornering in a vehicle. Stiffness of body-in-white is the basic characteristic of a car body, and it is closely related to the full-vehicle-level performance such as body durability, ride and handling, etc. There have been many attempts to correlate body stiffness to full-vehicle-level performance, and studying the relationship between torsional body stiffness and durability has been the popular topic among others. In general, it is believed to be true that bodies with high torsional stiffness exhibit good durability performance, and in many cases this assumption seems to be verified. However, not all cases are true to this assumption. In this paper, relationship between torsional body stiffness and body durability has been closely studied.

To meet the indoor air quality guideline of newly manufactured vehicles in Korea, China, and other countries, low formaldehyde grade POM (Polyoxymethylene) is used for interior parts essentially. In this paper, formaldehyde scavengers from of 2 commercial low formaldehyde grade POM pellets were identified by LC-MS (Liquid chromatograph-Mass spectrometer) as sebacic dihydrazide and dodecanedioic dihydrazide respectively. The reaction products between formaldehyde and formaldehyde scavengers were also detected, which were converted from hydrazide to hydrazone. So, this kind of additive would be gradually consumed by repetitive molding process or exposure to heat according to formaldehyde emission increase. We are expecting to apply this analytical method and result for quality control and benchmark of low formaldehyde grade POM.

It is known that SEA is a rapid and simple methodology for analyzing complex vibroacoustic systems. However, the SEA principle is not always valid and one has to be careful about the physical conditions at which the SEA principle is acceptable. In this study, the appropriate damping loss factor of the vehicle interior cavity is studied in the viewpoint of the modal overlap factor of the cavity and the decay per mean free path (DMFP) of the cavity. Virtual SEA tests are performed with an FE model combination, which is suggested by a previous study of Stelzer et al. for the simulation of the sound transmission loss (STL) of vehicle panel structure. The FE model combination is consisting of the body in white (BIW), an acoustical-excited hemisphere-shaped exterior cavity, and the interior cavity. It is found that the DMFP of the interior cavity is appropriate between 0.5 ~ 1 dB for applying SEA principle.

Current developments in the automotive industry such as electrification and consistent lightweight construction increasingly enable the application of active control systems for the further reduction of noise in vehicles. As different stochastic noise sources such as rolling and wind noise as well as noise radiated by the ventilation system are becoming more noticeable and as passive measures for NVH optimization tend to be heavy and construction-space intensive, current research activities focus on active reduction of noise caused by the latter mentioned sources. This paper illustrates the development, implementation and experimental investigation of an active noise control system integrated into the ventilation duct system of a passenger car.

This paper focuses on the optimization of the cross-section of a panel type impact door beam. The key parameters of the cross-section of the beam were artificially changed by using a geometry morphing tool FCM (Fast Concept Modeler), which is plugged in to CATIA. Then, the metamodel of FE (Finite Element) analysis results was created and optimized using LS-OPT. The ANOVA (Analysis of Variance) analysis of results was carried out to find the factor of weight reduction. Finally, a new cross section concept was proposed to overcome the limitation of old structure. The optimization was carried out for the beam with the final cross-section to have 10 % or more reduction in total weight.

The software must be verified and optimized from time to time to ensure system performance quality from the development process. Because the later you discover performance issues, the greater the cost of performance improvements, along with the extent to which they are fixed in the source code. In particular, performance problems due to poor system design should be identified and corrected as soon as possible. Also, as development progresses, source code added for new features and modified by bugs can potentially increase system resource usage or worsen responsiveness. Therefore, the development process needs to periodically measure, analyze, and improve system performance. This paper introduces the system-wide performance analyzer and explains how to use it to measure and analyze the performance of the infotainment system for performance management and improvement.

The digital evaluation process of vehicle-seat dimensions is an efficient and cost-effective way to achieve better seating comfort and proper fit. The present study is intended to quantify the statistical relationships between seat dimensions (e.g., insert width and bolster height defined at SAE J2732) and subjective seat fit (e.g., too tight, right fit, or too wide). Subjective fit evaluations for 45 different vehicle seats and the corresponding vehicle seat dimensions at various cross-sectional planes were collected by seat engineers (experts). The best subset logistic regression analyses were applied to quantify the relationships between the collected expert evaluations and seat dimensions at each cross-sectional plane. As a result, significant seat dimensions on the seat fit were identified and their statistical relationships were quantified as regression coefficients.

The friction properties related to squeal noise was analyzed with the development histories and simplified computational method. Firstly, the development histories were investigated especially focusing on the case which the friction materials were modified to improve squeal noise occurrence. Based on the histories, the friction properties of selected friction materials were newly measured using dynamometer. The average friction coefficient levels, torque oscillations, the increment of friction coefficient during full-stop, and etc. were compared with the squeal noise occurrence, and the results showed that increase of friction properties cause production of squeal noise. The result suggested that the size of friction energy was important factors related to triggering the squeal noise. Also, the contact conditions between rotor disc and friction materials were significant factors deciding the noise occurrence.

The dimensions of an automobile seat are important factors affecting a driver’s seating comfort, fit, and satisfaction. In this regard, seat engineers put forth tremendous efforts to evaluate the dimensions of a product seat until the dimensions are consistent with the design reference in a computer aided design (CAD). However, the existing evaluation process is heavily reliant on seat engineers’ manual tasks which are highly repetitive, labor intensive, and time-demanding tasks. The objective of this study is to develop an automated system that can efficiently and accurately evaluate seat products by comparing estimated seat dimensions from a CAD model or a 3D scan model. By using the developed system, the evaluation time for comparing 18 seat dimensions on CAD and scan models has been substantially reduced to less than one minute, which is 99% time saving compared to two hours in the manual process.

Conventional EPS (Electric Power Steering) systems are operated by one type of steering tuning map set by steering test drivers before being released to customers. That is, the steering efforts can't change in many different driving conditions such as road conditions (low mu, high mu and unpaved roads) or some specific driving conditions (sudden stopping, entering into EPS failure modes and full accelerating). Those conditions can't give drivers consistent steering efforts. This paper approached the new concept technology detecting those conditions by using vehicle and EPS sensors such as tire wheel speeds, vehicle speed, steering angle, steering torque, steering speed and so on. After detecting those conditions and judging what the best steering efforts for safe vehicle driving are, EPS systems automatically can be changed with the steering friction level and selection of steering optimized mapping on several conditions.

Impact resistance of plastic underbody parts was studied using simulated injection-molded specimen which can be tested according to different types of material used, injection molding variants like position and number of injection molding gates, and features of ribs. Material applied was glass fiber reinforced polyamide which can be used in underbody parts. Test was performed using several combinations of injection molding gates and rib types. From the test result, optimal design guide for plastic underbody parts was determined. Also, new high impact resistant plastic material made of glass fiber reinforced polyamide 66 (PA66) and polyamide 6 (PA6) alloy was developed and the material properties useful for CAE were determined. As a case study, oil pan and muffler housing were designed following the optimal design guide and CAE. And the reliability of the sample muffler housing designed was verified.