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Recent field data have shown that the occupant protection in vehicle rear seats failed to keep pace with advances in the front seats likely due to the lack of advanced safety technologies. The objective of this study was to optimize advanced restraint systems for protecting rear seat occupants with a range of body sizes under different frontal crash pulses. Three series of sled tests (baseline tests, advanced restraint trial tests, and final tests), MADYMO model validations against a subset of the sled tests, and design optimizations using the validated models were conducted to investigate rear seat occupant protection with 4 Anthropomorphic Test Devices (ATDs) and 2 crash pulses.

Engine cooling module air flows depend on package components and vehicle front end geometry. For years, in the early stages of vehicle development, front end geometry air flows were determined from 3/8 scale models or retrofit of similar existing vehicles. As time to market has become much shorter, finite element modeling of air flows is the only tool available. This paper describes how finite element simulations of front end air flows can be run early in the development program independent of any specific engine cooling module configuration and then coupled with traditional one-dimensional component performance models to predict cooling module air flows. The CFD simulation thus replaces the previous scale model testing process. The CFD simulations are used to determine the two parameters that characterize the front end geometry flow resistance (recovery coefficient and internal loss coefficient).

An automated process was developed for the calibration of numerical aftertreatment models. The chemical kinetic mechanism examined in this case was part of a simplified SCR model. The process adopted for calibrating the SCR model was based on a micro-population multi-objective genetic algorithm. The algorithm developed was used to calibrate the SCR model using data derived from another, more detailed model to ensure that the evaluation focused only on the effectiveness of the calibration process and was not affected by issues of experimental inaccuracies or details of the model chemistry involved.

Premixed Charge Compression Ignition (PCCI), a Low Temperature Combustion (LTC) strategy for diesel engines is of increasing interest due to its potential to simultaneously reduce soot and NOx emissions. However, the influence of mixture preparation on combustion phasing and heat release rate in LTC is not fully understood. In the present study, the influence of injection timing on mixture preparation, combustion and emissions in PCCI mode is investigated by experimental and computational methods. A sequential coupling approach of 3D CFD with a Stochastic Reactor Model (SRM) is used to simulate the PCCI engine. The SRM accounts for detailed chemical kinetics, convective heat transfer and turbulent micro-mixing. In this integrated approach, the temperature-equivalence ratio statistics obtained using KIVA 3V are mapped onto the stochastic particle ensemble used in the SRM.

With recent increases in global fuel prices there has become a growing interest in expanding the use of diesel engines in the transportation industry. However, new engine development is costly and time intensive, requiring many hours of expensive engine tests. The ability to accurately predict an engine's performance based on existing models would reduce the expense involved in creating a new engine of different size. In the present study experimental results from two single-cylinder direct injection diesel engines were used to examine previously developed engine scaling models. The first scaling model was based on an equal spray penetration correlation. The second model considered both equal spray penetration and flame lift-off length. The engines used were a heavy-duty Caterpillar engine with a 2.44L displacement and a light-duty GM engine with a 0.48L displacement.

Aerodynamic had played a primary role in high performance car since the late 1960s, when introduction of the first inverted wings appeared in some formulas. Race car aerodynamic optimisation is one of the most important reason behind the car performance. Moreover, for high performance car using naturally aspired engine, car aerodynamic has a strong influence also on engine performance by its influence on the engine airbox. To improve engine performance, a detailed fluid dynamic analysis of the car/airbox interaction is highly recommended. To design an airbox geometry, a wide range of aspects must be considered because its geometry influences both car chassis design and whole car aerodynamic efficiency. To study the unsteady fluid dynamic phenomena inside an airbox, numerical approach could be considered as the best way to reach a complete integration between chassis, car aerodynamic design, and airbox design.

How can car designers evaluate device’s position inside a car today? Today only subjective tests or “reachability” tests are made to assess if a generic user is able to reach devices, but it’s no longer enough. The aim of this study is to identify an instrument (index) that is able to provide a numerical information about the discomfort level connected with a posture that is kept inside a car to reach a device, by this instrument it should be possible not only judge a posture, but also compare different solutions and get rapid and accurate evaluations. In the state of the art there are many indexes developed to evaluate postural comfort (like RULA, REBA and LUBA [3, 4, 5]) but none of them has been realized to evaluate postures’ conditions that can be detected inside a car, so their evaluations cannot be acceptable.

A realistic modeling of the wall heat transfer is essential for an accurate analysis and simulation of the working cycle of internal combustion engines. Empirical heat transfer formulations still dominate the application in engine process simulations because of their simplicity. However, experiments have shown that existing correlations do not provide satisfactory results for all the possible operation modes of hydrogen internal combustion engines. This paper describes the application of a flow field-based heat transfer model according to Schubert et al. [1]. The models strength is a more realistic description of the required characteristic velocity; considering the influence of the injection on the global turbulence and on the in-cylinder flow field results in a better prediction of the wall heat transfer during the compression stroke and for operations with multiple injections. Further an empirical hypothesis on the turbulence generation during combustion is presented.

LCDs are effective to display abundant information in a compact space. Therefore, the use of TFT or DOT metric displays in dashboard instrument display is getting popular in recent years. However, it is important issue for car makers how to let users know information about vehicle functions or outside environment and manage plentiful information. In this paper, the Rapid Control Prototyping (RCP) tool is proposed to design and standardize HMI logic associated with display contents in TFT or dot type LCD applied to an instrument cluster. In addition, it is possible to estimate HMI logic in advance by using this RCP. By this process, we can minimize the design and validation time of the vehicle specific HMI logic and improve the quality. As a result, we can dramatically reduce the total period of developing an instrument cluster.

Optimization of the engine cold start is critical for gasoline direct injection (GDI) engines to meet increasingly stringent emission regulations, since the emissions during the first 20 seconds of the cold start constitute more than 80% of the hydrocarbon (HC) emissions for the entire EPA FTP75 drive cycle. However, Direct Injection Spark Ignition (DISI) engine cold start optimization is very challenging due to the rapidly changing engine speed, cold thermal environment and low cranking fuel pressure. One approach to reduce HC emissions for DISI engines is to adopt retarded spark so that engines generate high heat fluxes for faster catalyst light-off during the cold idle. This approach typically degrades the engine combustion stability and presents additional challenges to the engine cold start. This paper describes a CFD modeling based approach to address these challenges for the Ford 3.5L V6 EcoBoost engine cold start.

In order to detect degradation of engine oil lubricant, bench testing along with a number of diesel-powered Ford trucks were instruments and tested. The purpose of the bench testing was primarily to determine performance aspects such as repeatability, hysteresis effects and so on. Vehicle testing was conducted by designing and installing a separate oil reservoir along with a circulation system which was mounted in the vicinity of the oil pan. An innovative oil sensor was directly installed on the reservoir which can measure five (5) independent oil parameters (viscosity, density, permittivity, conductance, temperature). In addition, the concept is capable of detecting the oil level continuously during normal engine operation. The sensing system consists of an ultrasonic transducer for the oil level detection as well as a Tuning Fork mechanical resonator for the oil condition measurement.

Engine operating strategies typically geared towards higher fuel economy and lower NOx widely affect exhaust composition and temperature. These exhaust variables critically drive the performance of After Treatment (AT) components, and hence should guide their screening and selection. Towards this end, the effect of H2 level in diesel exhaust on the performance of a Diesel Oxidation Catalyst (DOC) was studied using flow reactor experiments, vehicle emission measurements and mathematical models. Vehicle chassis dynamometer data showed that exhaust from light-duty and heavy-duty diesel trucks contained very little to almost no H2 (FTP average CO/H2 ∼ 40 to 70) as compared to that of a gasoline car exhaust (FTP average CO/H2 ∼ 3). Two identical flow reactor experiments, one with H2 (at CO/H2 ∼ 3) and another with no H2 in the feed were designed to screen DOCs under simulated feed gas conditions that mimicked these two extremes in the exhaust H2 levels.

Selective catalytic reduction (SCR) is allowing diesel engines to reach NOx emission levels which are unachievable in-cylinder. This technology is still evolving, and new catalyst formulations which provide higher performance and greater durability continue to be developed. Usually, their performance is measured on a flow reactor using ammonia as the reductant. However, in mobile applications a urea-water solution is used instead, and urea decomposition by thermolysis and hydrolysis provides the required ammonia to the catalyst. It is well known that urea decomposition is incomplete by the inlet face of the converter, and this is at least one reason why on-engine performance is generally lower than would be expected from reactor tests. Previous modeling of urea-water droplets has focused on developing detailed sub-models that can be implemented into computational fluid dynamics (CFD) codes.

Diesel Particulate Filters (DPF) are widely used to meet 2007 and beyond EPA Particulate Matter (PM) emissions requirements. During the soot loading process, soot is collected inside a porous wall and eventually forms a soot cake layer on the surface of the DPF inlet channel walls. A densely packaged soot layer and reduced pore size due to Particulate Matter (PM) deposition will reduce overall DPF wall permeability which results in increasing pressure drop across the DPF substrate. A regeneration process needs to be enacted to burn out all the soot collected inside the DPF. Soot mass is not always evenly distributed as the distribution is affected by the flow and temperature distribution at the DPF inlet. As a result, the heat release which is determined by the burn rate is locally dependent. High temperature gradients are often found inside DPF substrate as a result of these locally dependent burn rates.

In this work a detailed model to simulate the transient behavior of catalytic converters is presented. The model is able to predict the unsteady and reacting flows in the exhaust ducts, by solving the system of conservation equations of mass, momentum, energy and transport of reacting chemical species. The en-gine and the intake system have not been included in the simulation, imposing the measured values of mass flow, gas temperature and chemical composition as a boundary condition at the inlet of the exhaust system. A detailed analysis of the diffusion stage triggering is proposed along with simplifications of the physics, finalized to the reduction of the calculation time. Submodels for water condensation and its following evaporation on the monolith surface have been taken into account as well as oxygen storage promoted by ceria oxides.

A thorough understanding of vehicle exhaust aftertreatment system performance requires time-resolved emissions measurements that accurately follow driving transients, and that are correctly time-aligned with exhaust temperature and flow measurements. The transient response of conventional gas analyzers is characterized by both a time delay and an attenuation of high-frequency signal components. The distortion that this imposes on transient emissions measurements causes significant errors in instantaneous calculations of aftertreatment system efficiency, and thus in modal mass analysis. This creates difficulties in mathematical modeling of emissions system performance and in optimization of powertrain control strategies, leading to suboptimal aftertreatment system designs. A mathematical method is presented which improves the response time of emissions measurements. This begins with development of a model of gas transport and mixing within the sampling and measurement system.

Empirical models for engine-out oxides of Nitrogen (NOx) and smoke emissions have been developed for the purpose of minimizing transient emissions while maintaining transient response. Three major issues have been addressed: data acquisition, data processing and modeling method. Real and virtual transient parameters have been identified for acquisition. Accounting for the phase shift between transient engine events and transient emission measurements has been shown to be very important to the quality of model predictions. Several methods have been employed to account for the transient transport delays and sensor lags which constitute the phase shift. Finally several different empirical modeling methods have been used to determine the most suitable modeling method for transient emissions. These modeling methods include several kinds of neural networks, global regression and localized regression.

A promising SCR-only solution is presented to meet post-2010 NOx emission targets for heavy duty applications. The proposed concept is based on an engine from a EURO IV SCR application, which is considered optimal with respect to fuel economy and costs. The addition of advanced SCR after treatment comprising a standard and a close-coupled SCR catalyst offers a feasible emission solution, especially suited for EURO VI. In this paper, results of a simulation study are presented. This study concentrates on optimizing SCR deNOx performance. Simulation results of cold start FTP and WHTC test cycles are presented to demonstrate the potential of the close-coupled SCR concept. Comparison with measured engine out emissions of an EGR engine shows that a close-coupled SCR catalyst potentially has NOx reduction performance as good as EGR. Practical issues regarding the use of an SCR catalyst in close-coupled position will be addressed, as well as engine and exhaust layout.

Porous materials are extensively used in the construction of automotive sound package parts, due to their intrinsic capability of dissipating energy through different mechanisms. The issue related to the optimization of sound package parts (in terms of weight, cost, performances) has led to the need of models suitable for the analysis of porous materials' dynamical behavior and for this, along the years, several analytical and numerical models were proposed, all based on the system of equations initially developed by Biot. In particular, since about 10 years, FE implementations of Biot's system of equations have been available in commercial software programs but their application to sound package parts has been limited to a few isolated cases. This is due, partially at least, to the difficulty of smoothly integrating this type of analyses into the virtual NVH vehicle development.

NVH refinement is an important aspect of the powertrain development and vehicle integration process. The depletion of fossil-based fuels and increase in price of gasoline have prompted most vehicle manufacturers to embrace propulsion technologies with varying degrees and types of hybridization. Many different hybrid vehicle systems are either on the market, or under development, even up to all-electric vehicles. Each hybrid vehicle configuration brings unique NVH challenges that result from a variety of sources. This paper begins with an introductory discussion of hybrid propulsion technologies and associated unique vehicle NVH challenges inherent in the operation of such hybrid vehicles. Following this, the paper outlines a two-dimensional landscape of typical customer vehicle maneuvers mapped against hybrid electric vehicle (HEV) operational modes.