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High frequency wind noise caused by turbulent flow around the front pillars of a vehicle is an important factor for customer perception of ride comfort. In order to reduce undesirable interior wind noise during vehicle development process, a calculation and visualization method for exterior wind noise with an acceptable computational cost and adequate accuracy is required. In this paper an index for prediction of the strength of exterior wind noise, referred to as Exterior Noise Power (ENP), is developed based on an assumption that the acoustic power of exterior wind noise can be approximated by the far field acoustic power radiated from vehicle surface. Using the well-known Curle’s equation, ENP can be represented as a surface integral of an acoustic intensity distribution, referred to as Exterior Noise Power Distribution (ENPD). ENPD is estimated from turbulent surface pressure fluctuation and mean convective velocity in the vicinity of the vehicle surface.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

As part of the International Lubricant Standardization and Approval Committee's (ILSAC) goal of developing a global automatic transmission fluid (ATF) specification, members have been evaluating test methods that are currently used by various automotive manufacturers for qualifying ATF for use in their respective transmissions. This report deals with comparing test methods used for determining torque capacity in friction systems (shifting clutches). Three test methods were compared, the Plate Friction Test from the General Motors DEXRON®-III Specification, the Friction Durability Test from the Ford MERCON® Specification, and the Japanese Automotive Manufacturers Association Friction Test - JASO Method 348-95. Eight different fluids were evaluated. Friction parameters used in the comparison were breakaway friction, dynamic friction torque at midpoint and the end of engagement, and the ratio of end torque to midpoint torque.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

This paper presents a unified modeling environment to simulate vehicle driving and powertrain operations within the context of the surrounding environment, including interactions between vehicles and between vehicles and the road. The goal of this framework is to facilitate the analysis of the energy impacts of vehicle connectivity and automation, as well as the development of eco-driving algorithms. Connectivity and automation indeed provide the potential to use information about the environment and future driving to minimize energy consumption. To achieve this goal, the designers of eco-driving control strategies need to simulate a wide range of driving situations, including the interactions with other vehicles and the infrastructure in a closed-loop fashion.

A new material recycling technology for crosslinked rubber was developed using the continuous reactive processing method. In this process of producing reclaimed rubber, breakage of crosslinking points in the crosslinked rubber occurs selectively under the controls of shear stress, reaction temperature, and internal pressure in a modular screw type reactor. Deodorization during the process has also become possible by a newly developed method. The reclaimed rubber obtained from rubber waste generated from both automobile manufacturing products and post-consumer products shows excellent mechanical properties applicable to new rubber compounds. Furthermore, an enhanced rubber recycling process for producing thermoplastic elastomer (TPE) based on rubber waste has been established. The obtained TPE exhibits highly recoverable rubber elasticity and mechanical properties comparable to commercial TPE.

In this study, a new practical design method (tool) for engine sound quality in a car interior is proposed. The tool can automatically create the target interior sound using the psychoacoustic index ‘powerfulness’ based on subjective tests. Moreover, it can calculate the intake noise characteristic to create the target interior sound and select the suitable intake specification from the prepared database. By using this method sound engineering can be easily and effectively carried out without manufacturing an experimental car.

A new 4.0 liter V8 engine, 1UZ-FE, has been developed for the luxury sedan, LEXUS LS400. The engine has 4 camshafts and 32 valves, and weighs only 195 kg (430 lbs) having many light alloy components and carefully designed configurations. The appropriate engine displacement and high technology adopted throughout from design to manufacturing process enable the LS400 to run powerfully with excellent fuel economy and a pleasant sounds. It develops 250HP at 5600 rpm and 260ft-lbs of torque at 4400 rpm, and its fuel economy figure, well exceeds the EPA's tax charge level of 22.5mpg. These figures have been achieved through the newest technologies applied to every part of the design, such as: Well studied intake and exhaust systems, centrally located spark plug in the TOYOTA original four-valve combustion chamber, which has a narrow valve including angle, and low friction components like aluminum alloy valve lifters and well balanced moving parts.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

A process to recover carbon fibers from obsolete polymer matrix composite (PMC) materials has been developed. Carbon fibers have been recovered from samples containing urethane-based or epoxy-based substrates. An experimental parametric study conducted on both the bench-scale and the pilot-scale has been done to determine the least-cost process conditions. Based on this study, we have evaluated process economics that suggested a payback of about one year. This process is also applicable to polymer matrix composite materials made with thermoplastic substrates. This paper presents the results of the experimental testing campaign and the results of the process economic analysis.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

As connectivity and sensing technologies become more mature, automated vehicles can predict future driving situations and utilize this information to drive more energy-efficiently than human-driven vehicles. However, future information beyond the limited connectivity and sensing range is difficult to predict and utilize, limiting the energy-saving potential of energy-efficient driving. Thus, we combine a conventional speed optimization planner, developed in our previous work, and reinforcement learning to propose a real-time intelligent speed optimization planner for connected and automated vehicles. We briefly summarize the conventional speed optimization planner with limited information, based on closed-form energy-optimal solutions, and present its multiple parameters that determine reference speed trajectories.

Merging a CAE shape optimization system and a concept Taguchi method SN-ratio index, a robustness-focused automated shape optimization method has been developed. Applying this method to diesel intake ports, with mold position tolerance set as the error factor, SN-ratio was defined for swirl stability. As a result of the optimization provided by a multi-objective genetic algorithm, simultaneous improvement of flux, swirl rotation and SN ratio was achieved.

Statistical Energy Analysis (SEA) is a promising tool for developing an efficient sound package design for reducing airborne interior noise at high frequencies. The optimal sound package, however, is not directly predicted by using the SEA vehicle model alone and therefore requires parametric studies of sound package configurations. This paper describes an effective method for using SEA modeling to achieve the desired interior noise level targets. A mathematical model, expressed by one equation, is derived on the assumption that the directions of the power flows are known in the SEA model. This equation describes the relationship between sound package properties and the resulting interior noise level. Using the relationship between weight and performance of sound package, an efficient configuration can be determined. The predicted sound pressure level of the vehicle interior with the optimized sound package correlated well to the experimental data for the case presented in this paper.

In this paper, a sectional soot model coupled to a tabulated combustion model is compared with measurements from an experimental engine database. The sectional soot model, based on the work of Vervisch-Klakjic (Ph.D. thesis, Ecole Centrale Paris, Paris, 2011) and Netzell et al. (P. Combust. Inst., 31(1):667-674, 2007), has been implemented into IFPC3D (Bohbot et al., Oil Gas Sci Technol, 64(3):309-335, 2009), a 3D RANS solver. It enables a complex modeling of soot particles evolution, in a 3D Diesel simulation. Five distinct source terms are applied to each soot section at any time and any location of the flow. The inputs of the soot model are provided by a tabulated combustion model derived from the Engine Approximated Diffusion Flame (EADF) one (Michel and Colin, Int. J. Engine Res., 2013) and specifically modified to include the minor species required by the soot model.

In this paper, a new physics-based model for the prediction of NOx emissions produced by diesel engines is presented. The aim of this work is to provide a reference model for the validation of control strategies and NOx estimators. The model describes the NOx production in the burned gas zone where the burned gas temperature sub-model is adapted to be generic and tunable. The model consists of three main sub-models for the estimation of the burned gas temperature, the concentration of the species in the burned gases and the NOx formation, respectively. A new model for estimating the burned gas temperature, known to have a strong impact on thermal NOx formation rate, is proposed. The model depends on the intake burned gas ratio and the combustion phasing computed from the cylinder pressure. This model has a limited number of calibration parameters identified so that NOx model output matches with experimental data measured in a four-cylinder, four-stroke, direct-injection diesel engine.

This work presents a simple fan model that is based on the actuator disk approximation, and the blade element and vortex theory of a propeller. A set of equations are derived that require as input the rotational speed of the fan, geometric fan data, and the lift and drag coefficients of the blades. These equations are solved iteratively to obtain the body forces generated by the fan in the axial and circumferential directions. These forces are used as momentum sources in a CFD code to simulate the effect of the fan in an underhood thermal management simulation. To validate this fan model, a fan experiment was simulated. The model was incorporated into the CFD code STAR-CD and predictions were generated for axial and circumferential air velocities at different radial positions and at different planes downstream of the fan. The agreement between experimental measurements and predictions is good.

Many efforts have been made to understand the mechanism of whiplash injury. Recently, the cervical facet joint capsules have been focused on as a potential site of injury. An experimental approach has been taken to analyze the vertebral motion and to estimate joint capsule stretch that was thought to be a potential cause of pain. The purpose of this study is to analyze the kinematics of the cervical facet joint using a human FE model in order to better understand the injury mechanism. The Total Human Model for Safety (THUMS) was used to visually analyze the local and global kinematics of the spine. Soft tissues in the neck were newly modeled and introduced into THUMS for estimating the loading level in rear impacts. The model was first validated against human test data in the literature by comparing vertebrae motion as well as head and neck responses. Joint capsule strain was estimated from a maximum principal strain output from the elements representing the capsule tissues.