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Over the past decade, there have been many efforts to generate engine sound inside the cabin either in reducing way or in enhancing way. To reduce the engine noise, the passive way, such as sound absorption or sound insulation, was widely used but it has a limitation on its reduction performance. In recent days, with the development of signal processing technology, ANC (Active Noise Control) is been used to reduce the engine noise inside the cabin. On the other hand, technologies such as ASD (Active Sound Design) and ESG (Engine Sound Generator) have been used to generate the engine sound inside the vehicle. In the last ISNVH, Hyundai Motor Company newly introduced ESEV (Engine Sound by Engine Vibration) technology. This paper describes the ESEV Plus Minus that uses engine vibration to not only enhance the certain engine order components but reduce the other components at the same time. Consequently, this technology would produce a much more diverse engine sound.

Unpredictable faults oriented from ambiguous reasons could occur in an engine of a vehicle. However, there are some symptoms from which an engine is working abnormally before the engine is stalled by faults. In this paper, methods for diagnosis of engine faults by using vibrations are proposed. Through bench tests, to extract features for fault diagnosis, various samples with normal and abnormal conditions are prepared and vibration signals from the block of an engine are measured and analyzed. To consider cost and performance of a sensor, vibrations from a knock sensor signal as well as accelerometers are analyzed. Measured vibration signals are synchronized with signal of the crank position sensor and analyzed to detect which event is involved. Modulation analysis and Hilbert transform are applied to extract features representing the symptoms of engine faults and to indicate when the abnormal event happens, respectively.

Active Sound Design (ASD) allows the Personalized Engine Sound System to be implemented for different types of vehicles and in different geographical regions. While this process is possible, it requires a lot of on-road tuning and therefore is very time consuming. This study presents an efficient way of tuning ASD sounds based on binaural synthesis in a lab environment instead of on-road tuning. The on-road vehicle operating sounds are reproduced by a desktop NVH simulator while the binaural ASD sounds are synthesized by convolving measured Binaural Vehicle Impulse Responses with the output of ASD multi-channel amplifier in real time. A set of binaural recordings on road are compared with the reproduced sound in the lab environment. The comparison results showed the validity of the proposed method for ASD. The main advantage of this approach is the possibility of back-to-back comparison across different ASD tunings.

This paper discusses a technology for reducing the gas flow noise generated from the noise of the vehicle, especially the exhaust system. The primary function of the heat protector is thermal shutdown. However, due to the increase in engine power, downsizing of engines, and the rise of consumer's eye level, solutions about noise are now emphasized. To meet these needs, a new concept of heat protector manufacturing technology is required. A key component of this technology is the manufacturing technology of three-ply composite board which can absorb sound from the existing sound insulation aluminum heat protector. For this purpose, mold technology for punching aluminum sheet, optimization technique for punching effect, specific pattern design for high-strength/high-forming, sound absorbing material selection and composite sheet molding technology, and noise vibration reduction mounting technology for plate joining were developed.

This study was conducted to develop and validate a multidimensional measure of shift quality as perceived by drivers during kick-down shift events for automatic transmission vehicles. As part of the first study, a survey was conducted among common drivers to identify primary factors used to describe subjective gear-shifting qualities. A factor analysis on the survey data revealed four semantic subdimensions. These subdimensions include responsiveness, smoothness, unperceivable, and strength. Based on the four descriptive terms, a measure with semantic scales on each subdimension was developed and used in an experiment as the second study. Twelve participants drove and evaluated five vehicles with different gear shifting patterns. Participants were asked to make kick-down events with two different driving intentions (mild vs. sporty) across three different speeds on actual roadway (local streets and highway).

This paper presents the influence of radiated noise from engine surface according to assembly condition between the engine block and oil pan. At the first, the force exciting the main bearing of cylinder block is calculated by using a multi-body dynamics model of the engine crankshaft. Secondly, the modal analysis is processed to obtain the mode contribution and modal participation factors for the FEM of a virtual cylinder block. Thirdly, the radiated noise from a structure is calculated by acoustic-FEM analysis. This structure is assembled by the virtual oil pan with a rigid connection method and a soft connection method. The sandwich panel connection model is used for the soft connection method. The sound radiated from this assemble structure is calculated according to two different connection properties respectively. The sound matrices for two results are compared using an objective method.

Structure-born vibrations are often required to be localized in a complex structure, but in such dispersive medium, the vibration wave propagates with speed dependent on frequency. This property of solid materials causes an adverse effect for localization of vibrational events. The cause behind such phenomenon is that the propagating wave envelope changes its phase delay and amplitude in time and space as it travels in dispersive medium. This problem was previously approached by filtering a signal to focus on frequencies of the wave propagating with a similar speed, with improved accuracy of cross-correlation results. However, application of this technique has not been researched for localization of vibrational sources. In this work we take advantage of filtering prior to cross-correlation calculation while using multiple sensors to indicate an approximate location of vibration sources.

In the automotive industry, various simulation-based analysis methods have been suggested and applied to reduce the time and cost required to develop the engine structure to improve the NVH performance of powertrain. This simulation is helpful to set the engine design concept in the initial phase of the powertrain development schedules. However, when using the conventional simulation method with a uniformed force, the simulation results sometimes show different results than the test results. Therefore, in this paper, we propose a method for predicting the radiated noise level of a diesel engine using actual combustion excitation force. Based on the analytical radiated noise development target, we identify the major components of the engine that are beyond this development target by in the frequency range. The components of the problem found in this way are reflected in the engine design of the early development stage to shorten the development time.

This ‘Motion-Sensor Moustick’ is a sort of new concept control device as if a combination of PC mouse and joystick. It has three simple buttons and a haptic wheel designed for a faster and easier use to learn the vehicle infotainment functions. In addition it has a motion sensor to call a menu via hand approach to change media channels or to display status with just a driver's hand motion within a certain distance. Also this development includes a new concept GUI(graphical user interface) which is compatible with the ‘Moustick’ device. This development could be very helpful to use a car infotainment system.

In order to align with net-zero CO2 ambitions, automotive OEMs have been developing increasingly sophisticated strategies to minimise the impact that combustion engines have on the environment. Intelligent thermal management systems to actively control coolant flow around the engine have a positive impact on friction generated in the power cylinder by improving the warmup rate of cylinder liners and heads. This increase in temperature results in an improved frictional performance and cycle averaged fuel consumption, but also increases the piston to liner clearances due to rapid warm up of the upper part of the cylinder head. These increased clearances can introduce piston slap noise and substantially degrade the NVH quality to unacceptable levels, particularly during warmup after soak at low ambient temperatures. Using analytical techniques, it is possible to model the thermo-structural and NVH response of the power cylinder with different warm up strategies.

A new pass-by noise test method has been introduced, in which engine speeds and loads are reduced (compared to the old test method) to better reflect real world driving behavior. New noise limits apply from 1 July 2016, and tighten by up to 4dB by 2026. The new test method is recognized internationally, and it is anticipated that the limits will also be adopted in most territories around the world. To achieve these tough new pass-by noise requirements, vehicle manufacturers need to address several important aspects of their products. Vehicle performance is critical to the test method, and is controlled by the full load engine torque curve, speed of response to accelerator pedal input, transmission type, overall gear ratios, tire rolling radius, and resistance due to friction and aerodynamic drag. Noise sources (exhaust, intake, powertrain, driveline, tires) and vehicle noise insulation are critical to the noise level radiated to the far-field.

It is known that the major source of rumbling noise the combustion force of an engine. The combustion force excites the engine and induces vibrations of the powertrain. These vibrations are then transferred to the body of the vehicle via its structural transfer path. Moreover, the vibrations of the vehicle’s body emit internal vibra-acoustic noise. This noise is often referred to as the rumbling noise due to the structural borne path. If there are structural resonances among the structural paths such as the engine, transmission, mount bracket, suspension, and the vehicle’s body, the rumbling noise could be amplified. To identify the major resonances of the structural transfer path, classical transfer path analysis (CTPA) has been traditionally utilized. The method has a significant limitation in that it is necessary to decouple the substructures to obtain the contact force between individual components and to identify the transfer path of the structure-borne sound.

A Head-Up Display (HUD) is electrical device that provides virtual images in front of driver. Virtual images are consists of various driving information. Because HUD uses optical system there exist image distortions with respect to image height and driver’s eye position. Image warping is image correction method that makes a geometrical change on image to minimize image distortions. In this paper to minimize image distortions, we use optical data driven warping matrix for each image height. But even though we applied data driven warping matrix, image distortions occur due to assemble and manufacturing tolerances when HUD is built. In this paper, we also suggest pre-warping method to minimize image distortions considering tolerances. We simulated 3 compensation functions to get rid of image distortions from the tolerances. By using proposed pre-warping method we could reduce maximum x, y distance by 31.5%, 39% and average distance by 32.2%, 27.9% of distortions.

The powertrain durability test mode often defines the method by reflecting figures such as frequency of use or severity, but in complex systems, durability is difficult to verify in real life conditions under simple conditions. Therefore, in this session, a new analysis method modeled for each driving unit is presented, rather than analyzing time series data in time to extract representative driving pattern from the perspective of the powertrain load reflecting driving situation and driver’s will by applying machine learning technique, and to develop realistic durability test evaluation mode.

This paper suggests a method to formulate the driveline torque command for vehicles that use electric motor as part of their sources for providing driving power. The shape of the driveline torque profile notably influences the drivability criteria of the vehicle, and among them, driveline NVH and responsiveness are often tradeoffs for each other. Hence the real-time computed driveline torque profiling (DTP) enables formulation of the effective torque command at any given time to simultaneously satisfy both NVH and responsiveness criteria. Such task is fulfilled by using a shaft distortion prediction model based on a motor speed observer. A compensation torque command based on the amount of shaft distortion is formulated to prevent the shaft distortion with minimum effort. The effectiveness of the suggested driveline torque profiling method is verified using an actual vehicle, and the vehicle NVH and responsiveness are numerically assessed for comparison.

An active sound design (ASD) technique enables the implementation of a specific sound in addition to the real engine/e-motor sound in a vehicle. However, it is difficult to satisfy the various needs of customers because it can provide only a few sounds designed by the manufacturer. This paper presents the method of providing the appropriate driving sound and soundscape in an electric vehicle according to the driver’s emotion and driving environment in real-time. For this purpose, it is studied how to construct a driving sound library from the various sound sources and how to recognize a driver's total emotion from the multi-modal data such as facial expression, heart rate, and electrodermal activity using the CNN and support vector machine algorithms. Then it is discussed how to generate the driving sound of electric vehicle according to the driver’s emotion.

With the electrification trend in the automotive industry, the main contributors to in-vehicle noise profile are represented by drivetrain, road and wind noise. To tackle the problem in an early stage, the industry is developing advanced techniques guaranteeing modularity and independent description of each contributor. Component-based Transfer Path Analysis (C-TPA) allows individual characterization of substructures that can be assembled into a virtual vehicle assembly, allowing the manufacturers to switch between different designs, to handle the increased number of vehicle variants and increasing complexity of products. A major challenge in this methodology is to describe the subsystem in its realistic operational boundary conditions and preload. Moreover, to measure such component, it should be free at the connection interfaces, which logically creates significant difficulties to create the required conditions during the test campaign.

Optimizing the specifications of the parts that make up the vehicle is essential to develop a high performance and quality vehicle with price competitiveness. Optimizing parts specifications for quality and affordability means optimizing various factors such as engineering design specifications and manufacturing processes of parts. This optimization process must be carried out in the early stages of development to maximize its effectiveness. Therefore, in this paper, we studied the methodology of building a database for parts of already developed vehicles and optimizing them on a data basis. A methodology for collecting, standardizing, and analyzing data was studied to define information necessary for specification optimization. In addition, AI technology was used to derive optimization specifications based on the 3D shape of the parts. Through this study, body parts specification optimization system using AI technology was developed.

As the mobility being developed becomes more complex and numerous, it is becoming difficult and inefficient to apply current vehicle-test-based development. To overcome this, research on combining test and simulation models has been actively conducted to perform objective and subjective evaluations more accurately and efficiently in the advance stage without a vehicle over the years. At first, test models for various systems such as tire, suspension and body were made compatible with simulation models by using various methodologies such as blocked forces, FBS decoupling, and Virtual Point Transformation (VPT). The second step was to objectively estimate road noise by using FBS coupling with system models and to deeply analyze transfer paths and system’s sensitivity. The results were verified by comparing with what was measured and analyzed on vehicle.

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.