Search Results

Connected and Autonomous Vehicles (CAV) rely on information obtained from sensors and communication to make decisions. In a Cooperative Vehicle Safety (CVS) system, information from remote vehicles (RV) is available at the host vehicle (HV) through the wireless network. Safety applications such as crash warning algorithms use this information to estimate the RV and HV states. However, this information is uncertain and sparse due to communication losses, limitations of communication protocols in high congestion scenarios, and perception errors caused by sensor limitations. In this paper we present a novel approach to improve the robustness of the CVS systems, by proposing an architecture that divide application and information/perception subsystems and a novel prediction method based on non-parametric Bayesian inference to mitigate the detrimental effect of data loss on the performance of safety applications.

The optimal control of anode H2 concentration in fuel cell is the key performance parameter for efficiency and durability of the fuel cell electric vehicle. Implementation of H2 concentration sensor in fuel processing system is the best option to achieve the optimal control operation, but the vulnerability of the chip in H2 concentration sensor to the moisture has not been overcome and no H2 concentration sensor for vehicle application is present in the world so far. Due to the immaturity of the H2 concentration sensor, a number of researches have been being made to keep the H2 concentration in the anode at certain level without H2 concentration sensors. However the effectiveness of those technologies has not been good to meet the design specification in all the operating range of the various driving cycles and environmental condition.

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.

Commercially available Third Generation Advanced High Strength Steels (GEN3 AHSS) are qualified by automakers worldwide. With an excellent combination of strength and ductility, GEN3 AHSS are cold-formable and have shown potential to replace press hardenable steels (PHS) in structural applications. With overall formability equivalent to 590DP, U. S. Steel 980 GEN3 AHSS (980 XG3™ AHSS) may achieve cold-formed component geometries similar to those achieved by hot-formed PHS. Furthermore 980 GEN3 AHSS demonstrates a substantial increase in post-forming yield strength due to the combined effects of work-hardening and bake-hardening-thereby contributing strongly toward crash energy management performance. The technical challenges and attributes of cold-formed 980 GEN3 AHSS are explored in this paper for an automotive rear rail application (currently PHS), including: formability analysis, wrinkling elimination and springback compensation.

A brake is a mechanical device that inhibits the motion by absorbing energy from a moving system. It is used for slowing or stopping a moving vehicle, wheel, axle, or to prevent its motion, most often accomplished by friction energy. Commonly, most brakes use friction between two surfaces pressed together to convert the kinetic energy of the moving object into heat, though other methods of energy conversion may be employed. If braking is repeated or sustained in high load or high-speed conditions, the motion will be unstable and can lead to a loss of stopping power because the disc capability for braking is not enough. These phenomena are generally defined as brake fading. Brake fade is caused by an overheating brake system. This paper describes the thermal modeling and process to predict the disk temperature under a condition which causes the fade characteristics.

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).

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.

Rising gas prices and increasingly stringent vehicle emissions standards have pushed automakers to increase fuel economy. Mass reduction is the most practical method to increase fuel economy of a vehicle. New materials and CAE technology allow for lightweight automotive components to be designed and manufactured, which outperform traditional component designs. Topology optimization and other design optimization techniques are widely used by designers to create lightweight structural automotive parts. Other design optimization techniques include free-size, gauge, and size optimization. These optimization techniques are typically used in sequence or independently during the design process. Performing various types of design optimization simultaneously is only practical in certain cases, where different parts of the structure have different manufacturing constraints.

Increasing fuel prices and escalating emissions standards, are leading car manufacturers to develop vehicles with higher fuel efficiency. Reducing the mass of the vehicle is one technique to improve fuel efficiency. Shifting from metals to composite materials is a promising approach for great reductions to the vehicle mass. As more composite parts are introduced into vehicles, the approach to joining components is changing and requiring more investigation. Metallic chassis components are traditionally joined with mechanical fasteners, while composites are generally joined with adhesives. In a collaboration between Queen’s University and KCarbon, an automotive composite crossmember is being developed. A variety of lap joint geometries were modeled into a the crossmember assembly for composite-composite joints. Finite element-based optimization methods were applied to reduce mass of the crossmember. The optimized masses showed a 5% difference between the three joint geometries analyzed

The flame propagation characteristic is one of the greatest factor that determines the performance of spark ignition (SI) engines. The in-cylinder flow dynamics is very significant in terms of flame propagation because of its direct influence on the flame shape, turbulent flame speed, and the ignition quality. A number of different techniques are available to optimize the in-cylinder flow and maximize the utilization of turbulence for faster combustion, and tumble enhancement by intake port geometry is one of them. It requires excessive computational expenses to evaluate multiple designs under wide range of operating conditions by 3D-CFD, therefore, a low-dimensional model would be more competitive in such design optimization process. This work suggests a new modification approach for typical 0D turbulence model to take account for the tumble generation during the intake process as well as the turbulence characteristics associated with it.

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.

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.

Limited fossil fuel resources, air pollution, and global warming all drive strengthening of fuel economy and vehicle emission standards globally. Much R&D continues to be dedicated to improve fuel efficiency of automobiles and to reduce exhaust gasses. These include improvement of engine/driveline performance for higher efficiency, development of alternative energy, and minimization of air resistance through aerodynamic design optimization. OEM weight reduction-focused research has extended into chassis components (steering knuckle, brakes, control arms, etc.) in sequence from body-in-white(BIW). Wheel bearings, one of the core components of a driveline and part of a vehicle’s unsprung mass, are also being required to reduce weight. Conventionally, wheel bearings have achieved “lightweighting” primarily through design optimization methods. They have been highly optimized today using steel based materials.

As demand for fuel efficiency rises, an increasing number of automotive companies are replacing their existing metal designs with carbon-fiber-reinforced polymer (CFRP) redesigns. Due to the handling and manufacturing processes associated with CFRP materials, engineers have more design freedom to create complex, light-weight designs, which would be infeasible to manufacture using metal. Additionally, it is likely that by redesigning with CFRP, many steel assemblies can be consolidated to significantly fewer parts, simplifying or potentially eliminating the assembly process. When designing an automotive crossmember using CFRP materials, designers often aim for a two-piece design (top and bottom), while utilizing reinforcement material where needed. The joining of these two pieces is typically accomplished with many mechanical fasteners and adhesives, significantly increasing the part count and the manufacturing complexity.

Fiber-reinforced plastics (FRPs), produced through injection molding, are increasingly preferred over steel in automotive applications due to their lightweight, moldability, and excellent physical properties. However, the expanding use of FRPs presents a critical challenge: deformation stability. The occurrence of warping significantly compromises the initial product quality due to challenges in part mounting and interference with surrounding parts. Consequently, mitigating warpage in FRP-based injection parts is paramount for achieving high-quality parts. In this study, we present a holistic approach to address warpage in injection-molded parts using FRP. We employed a systematic Design of Experiments (DOE) methodology to optimize materials, processes, and equipment, with a focus on reducing warpage, particularly for the exterior part. First, we optimized material using a mixture design in DOE, emphasizing reinforcements favorable for warpage mitigation.

This study deals with the fatigue life prediction methodology of welding simulation components involving arc welding. First, a method for deriving the cyclic deformation and fatigue properties of the weld metal (that is also called ER70S-3 in AWS, American Welding Standard) is explained using solid bar specimens. Then, welded tube specimens were used with two symmetric welds and subjected to axial, torsion, and combined in-phase and out-of-phase axial-torsion loads. In most previous studies the weld bead’s start/stop were arbitrarily removed by overlapping the starting and stop point. Because it can reduce fatigue data scatter. However, in this study make the two symmetric weld’s start/stops exposed to applying load. Because the shape of the weld bead generated after the welding process can act as a notch (Ex. root notch at weld start / Crater at weld stop) to an applied stress. Accordingly, they were intentionally designed to cause stress concentrations on start/stops.

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.

This study delves into the microstructural and mechanical characteristics of AlSi10Mg alloy produced through the Laser Powder Bed Fusion (L-PBF) method. The investigation identified optimal process parameters for AlSi10Mg alloy based on Volume Energy Density (VED). Manufacturing conditions in the L-PBF process involve factors like laser power, scan speed, hatching distance, and layer thickness. Generally, high laser power may lead to spattering, while low laser power can result in lack-of-fusion areas. Similarly, high scan speeds may cause lack-of-fusion, and low scan speeds can induce spattering. Ensuring the quality of specimens and parts necessitates optimizing these process parameters. To address the low elongation properties in the as-built condition, heat treatment was employed. The initial microstructure of AlSi10Mg alloy in its as-built state comprises a cell structure with α-Al cell walls and eutectic Si.