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In contrast to highway, there are some sections not well maintained in urban roads. In these sections, there may be faint lane marks or static obstacles due to construction or some other reasons. Therefore, an automated vehicle following system such as traffic jam assistant should consider these sections to guarantee the safety of the system. In order to achieve this purpose, a model predictive control (MPC) scheme has been developed. The objectives of MPC are to compute the sequence of optimal steering input for vehicle following with obstacle avoidance. For this, the MPC uses the lead vehicle's state and obstacle's position obtained by lidars. For this purpose, a simplified nonlinear model of the vehicle was used to predict the future evolution of the system. Based on this prediction, performance index is optimized under operating constraints at each time step. A test vehicle equipped with two lidars on left and right corner of the front bumper has been developed.

The assessment of the Transmission Loss (TL) of vehicle components at Low-Mid Frequencies generally raises difficulties associated to the physical mechanisms of the noise transmission through the automotive panel. As far as testing is concerned, it is common in the automotive industry to perform double room TL measurements of component baffled cut-outs, while numerical methods are rather applied when prototype or hardware variants are not available. Indeed, in the context of recent efforts for reduction of vehicle prototypes, the use of simulation is constantly challenged to deliver reliable means of decision during virtual design phase. While the Transfer matrix method is commonly and conveniently used at Mid-High frequencies for the calculation of a trimmed panel, the simulation of energy transfer at low frequencies must take into account modal interactions between the vehicle component and the acoustic environment.

The recent development pace of the automotive technology is so rapid worldwide. Especially in a green car, hybrid electric vehicles (HEVs) have been studied a lot due to their significant effects on the urban driving. In the vehicle energy management strategy study, the driving speed is assumed to be known in advance, however the speed is not given in a real world. Accordingly, the prediction of vehicle speed is very important. In this study, we study the prediction methodology for the speed prediction using deep learning. Based on the vehicle driving speed data, the supervised deep learning has been used and the speed prediction accuracy using deep learning shows accurate results comparing to the actual speed. The supervised deep learning is used which is suitable for driving cycle database. As a result, the speed prediction after few seconds is feasible.

Since the amount of emitted CO2 is directly related to car fuel economy, attention is being drawn to DISI (Direct-Injection Spark-Ignition) engines, which have better fuel economy than conventional gasoline engines. However, it has been a problem that the rich air-fuel mixtures associated with fuel films during cold starts due to spray impingement produce particulate matter (PM). In predicting soot formation, it is important to predict the mixture field precisely. Thus, accurate spray and film models are a prerequisite of the soot model. The previous models were well matched with low-speed collision conditions, such as those of diesel engines, which have a relatively high ambient pressure and long traveling distances. Droplets colliding at low velocities have an order of magnitude of kinetic energy similar to that of the sum of the surface tension energy and the critical energy at which the splash occurs.

For electrified vehicles, understanding the impact of temperature on vehicle control and performances becomes more important than before because the vehicle might consume more energy than conventional vehicles due to lack of the engine waste heat. Argonne has tested many advanced vehicles and analyzed the vehicle level control based on the test data. As part of its ongoing effort, Toyota Prius Plug-in Hybrid was tested in thermal environmental chamber, and the vehicle level control and performances are analyzed by observing the test results. The analysis results show that the control of the Plug-in Hybrid Electric Vehicle (PHEV) is similar with Prius Hybrid Electric Vehicle (HEV) when the vehicle is under a charge sustaining mode, and the vehicle tries to consume the electric energy first under a charge depleting mode.

The combustion process using two fuels with different reactivity, known as dual-fuel combustion or RCCI is mainly studied to reduce emissions while maintaining thermal efficiency compared to the conventional diesel combustion. Many studies have proven that dual-fuel combustion has a positive prospect in future combustion to achieve ultra-low engine-out emissions with high indicated thermal efficiency. However, a limitation on high-load expansion due to the higher maximum in-cylinder pressure rise rate (mPRR) is a main problem. Thus, it is important to establish the operating strategy and study the effect of in-cylinder flow motion with dual-fuel combustion to achieve a low mPRR and emissions while maintaining high-efficiency. In this research, the characteristics of gasoline-diesel dual-fuel combustion on different hardware were studied to verify the effect of the in-cylinder flow motion on dual-fuel combustion.

Two-mode hybrid architectures with three planetary gear sets and four clutches will bring both flexibility and complexity to energy management of powertrains. In order to take full advantage of the increased degrees of freedom, highly delicate operation strategies are needed. We develop transmission efficiency models for power-split modes, and present a mode shift strategy assuming no battery power. When battery load leveling is additionally considered, the respective optimal operation set for each mode can be obtained and compared to yield a mode shift algorithm for general hybrid operation situations. The investigation of the strategies shows how frequently each mode is used, and verifies the effectiveness of fixed gear operations. We check the validity of the strategies by applying the algorithm to dynamic optimization and by predicting how it works during an actual driving simulation.

This paper describes a driving control algorithm based on skid steering for a Robotic Vehicle with Articulated Suspension (RVAS). The driving control algorithm consists of four parts; speed controller for tracking of the desired speeds, yaw rate controller which computes a yaw moment input to track desired yaw rates, longitudinal tire force distribution which determines an optimal desired longitudinal tire force and wheel torque controller which determines a wheel torque command at each wheel to keep slip ratio at each wheel below a limit value as well as track the desired tire force. Longitudinal and vertical tire force estimators are designed for optimal tire force distribution and wheel slip control. The dynamic model of RVAS for simulation study is validated using vehicle test data.

Currently, the use of numerical and analytical tools during a vehicle development is extensive in the automotive industry. This assures that the required performance levels can be achieved from the early stages of development. However, there are some aspects of the vibro-acoustic performance of a vehicle that are rarely assessed through numerical or analytical analysis. An example is the modeling of sound transmission through vehicle sealing systems. In this case, most of the investigations have been done experimentally, and the analytical models available are not sufficiently accurate. In this paper, the modeling of the sound transmission through a vehicle door seal is presented. The study is an extension of a previous work in which the applicability of the Hybrid FE-SEA method was demonstrated for predicting the TL of sealing elements.

As speed of ground vehicle increases, there are increased concerns on the aerodynamic drag reduction of ground vehicle. Recently, synthetic jet is emerging as a promising active flow control technology for aerodynamic drag reduction. In this paper, we performed an experimental parametric study on synthetic jet for aerodynamic drag reduction of Ahmed model. Synthetic jet array is constructed by twelve synthetic jet actuators, and installed on two kinds of Ahmed models, of which slant angles are 25° and 35°. The jets are emanated between the roof and the rear slant surface. Jet angle, momentum coefficient, and driving frequency are changed to assess the effect of synthetic jet array on aerodynamic drag. To quantify the effect of synthetic jet, the aerodynamic drag and rear surface pressure are measured and analyzed. From the result, the effect of synthetic jet actuation on aerodynamic drag differs according to the slant angle of the body.

For diesel engines to meet current and future emissions levels, the amount of EGR required to reach these levels has increased dramatically. This increased EGR has posed big challenges for conventional turbocharger technology to meet the higher emissions requirements while maintaining or improving other vehicle attributes, to the extent that some OEMs resort to multiple turbocharger configurations. These configurations can include parallel, series sequential, or parallel - series turbocharger systems, which would inevitably run into other issues, such as cost, packaging, and thermal loss, etc. This study, as part of a U.S. Department of Energy (USDoE) sponsored research program, is focused on the experimental evaluation of the emission and performance of a modern diesel engine with an advanced single stage turbocharger.

Industrial requirements imply optimizing the development cycle, reducing manufacturing costs and reaching marketable product maturity as fast as possible. The design stage often involves multiple sites and various partners. In this context, the use of computer simulation becomes absolutely necessary to meet industrial needs. Nevertheless, this activity can be effective only if it is integrated correctly in the industrial organization. In the aeronautical and space systems industry, mechanical specifications often require the use of composites reinforced by continuous carbon fibers. The goal of this article is to describe how, on a time frame of nearly twenty years, a series of scientific and technical tasks were carried out in partnership in order to develop, validate and implement Resin Transfer Molding (RTM) flow simulation and cure analysis for high performance composites. The research stage started at the university in 1991.

As fuel injection strategies in spark-ignition (SI) engines have been diversified, inhomogeneous mixing of the fuel-air mixture can occur to varying extents during mixture preparation. In this study, we analyzed the effect of inhomogeneous mixing on the knocking characteristics of iso-octane and air mixture under a standardized fuel testing condition for research octane number (RON), based on ASTM D2699. For this purpose, we assumed that both lean spots and rich spots existed in unburned gas during compression stroke and flame propagation and calculated the thermodynamic state of the spots by using an in-house multi-zone, zero-dimensional SI engine model. Then, the ignition delay was measured over the derived thermodynamic profiles by using rapid compression machine (RCM), and we calculated ξ, the ratio of sound speed to auto-ignition propagation speed, based on Zel’dovich and Bradley’s ξ − ε theory to estimate knock intensity.

For the case of the in-plane vibration of a plate, the power is carried by shear and longitudinal waves generating an in-plane two-dimensional displacement field. The objective of this paper is to propose experimental techniques for the measurement of the in-plane vibration intensity (power flow per unit width of a cross section) of the plate. The theoretical basis is outlined for the experimental techniques. The experimental techniques have been implemented to measure the in-plane vibration intensity in the plate. The experimental results of the in-plane vibration intensity in the plate have been compared with the theoretical results. It is shown that the experimental techniques can be effectively used to measure the in-plane vibration intensity in the plate.

CAE capabilities have long been used for performing static and dynamic structural analysis during the seat design process. More recently, the soft parts of the seat including foams, trim and suspension have also been modeled with CAE. The purpose of this modeling is to better understand the physical phenomena which are involved in the sitting process, to enhance seat design knowledge, and to replace as much physical testing during the design process with virtual, CAE testing. This paper presents the first part of a multi-phased, both experimental and numerical project. The aim of this first stage is to assess the capabilities of a CAE methodology to predict FMVSS 202a backset. Based on CAD data, a finite element mesh of the seat was built. The mechanical behavior of all parts was characterized through experiments on material samples.

This paper presents the second part of a multi-phased, both experimental and numerical project, devoted to the use of Virtual Prototyping techniques for seat design. The aim of this stage is to assess the capabilities of a CAE methodology to predict some comfort-related mechanical parameters, such as overall hardness and plushness, as a base engineering approach to quantify an occupant perception of both long- and short-term comfort. For hardness, a simple human surrogate (SAE AM50 Buttock Form) is applied on the bottom cushion of a fully trimmed, current production FORD seat, following a load cycle. For initial softness, a round probe is indented at different locations of both backrest and bottom cushions, following loading cycles. The resulting load-deflection curves predicted by numerical simulation are in good agreement with the experimental ones.

This paper introduces a systematic wiring guideline which includes coupling noise calculation, wire layout design, and wire type selection methodologies. The coupling theory between wires has been introduced long time ago but it was not successfully applied to real automotive wiring design due to the complexity in the theory such as large number of parameters and many different conditions in automotive wiring environment. In this paper, the complexity is reduced by separating physical parameters and electrical parameters and identifying controllable parameters and given parameters. This paper first introduces parameters which are used in the coupling equations and automotive wiring design, then the coupling noise calculation method which uses the coupling equations is introduced. The systematic automotive wiring guideline which prevents noise problem in various design stage such as system filter design, wire layout design, wire type selection is introduced.

Modeling of unburned hydrocarbon oxidation in an SI engine was performed in engine condition using modified one-step oxidation model. The new one-step equation was developed by modifying the Arrhenius reaction rate coefficients of the conventional one-step model. The modified model was well matched with the results of detailed chemical reaction mechanism in terms of 90 % oxidation time of the fuel. In this modification, the effect of pressure and intermediate species in the burnt gas on the oxidation rate investigated and included in developed one-step model. The effect of pressure was also investigated and included as an additional multiplying factor in the reaction equation. To simulate the oxidation process of piston crevice hydrocarbons, a computational mesh was constructed with fine mesh density at the piston crevice region and the number of cell layers in cylinder was controlled according to the motion of piston.

This paper describes our development work for acceleration sensing modules for electronic stability program (ESP) applications. The accelerometer is fabricated using the unique sacrificial/bulk micromachining (SBM) process by us. The sensing modules are designed to measure low level accelerations accurately and be stable in an automotive environment. This paper describes the accelerometer design and fabrication, electronic circuits and PCB design, module assembly, and performances of the developed sensing module. The developed sensing module offers analog voltage output with ±1.5g dynamic range, 0.05% nonlinearity, >50Hz bandwidth and 1295mV/g scale factor. The module includes a CAN2.0A interface and yields good experimental performance when implemented on a CAN test server.

Characteristics of syngas combustion at various reforming ratios were studied numerically. The syngas was formed by the partial oxidation of methane to mainly hydrogen and carbon monoxide and cooled to ambient temperature. Stiochiometric and lean premixed flames of the mixtures of methane and the syngas were compared at the atmospheric temperature and pressure conditions. The adiabatic flame temperature decreased with the reforming ratio. The laminar burning velocity, however, increased with the reforming ratio. For stretched flames in a counterflow, the high temperature region was broadened with the reforming ratio. The maximum flame temperature decreased with the reforming ratio for the stoichiometric case, but increased for the lean case except for the region of very low stretch rate. The extinction stretch rate increased with the reforming ratio, implying that the syngas assisted flame is more resistance to turbulence level.