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In general for Vehicle-to-Vehicle (V2V) communication, message authentication is performed on every received wireless message by conducting verification for a valid signature, and only messages that have been successfully verified are processed further. In V2V safety communication, there are a large number of vehicles and each vehicle transmits safety messages frequently; therefore the number of received messages per second would be large. Thus authentication of each and every received message, for example based on the IEEE 1609.2 standard, is computationally very expensive and can only be carried out with expensive dedicated cryptographic hardware. An interesting observation is that most of these routine safety messages do not result in driver warnings or control actions since we expect that the safety system would be designed to provide warnings or control actions only when the threat of collision is high.

The initial presence and dynamic formation of internal voids in human body models have been subjects of discussion within the human body modeling community. The relevant physics of the human body are described and the importance of capturing this physics for modeling of internal organ interactions is demonstrated. Basic modeling concepts are discussed along with a proposal of simulation setups designed to verify model behavior in terms of volume and pressure between internal organs.

Measured vehicle loads have traditionally been used as the basis for development of component, subsystem and vehicle level durability tests. The use of measured loads posed challenges due to the availability of representative hardware, scheduling, and other factors. In addition, stress was placed on existing procedures and methods by aggressive product development timing, variety in tuning and equipment packages, and higher levels of design optimization. To meet these challenges, General Motors developed new processes and technical competencies which enabled the direct substitution of analytically synthesized loads for measured data. This process of Virtual Road Load Data Acquisition (vRLDA) enabled (a) conformance to shortened product development cycles, (b) greater consistency between design targets and validation requirements, and (c) more comprehensive data.

In order to assess the possible ways of energy transfer from the various sources of excitation in a vehicle assembly to a given target location, frequency based substructuring technique and transfer path analysis are used. These methods help to locate the most important energy transfer paths for a specific problem, and to evaluate their individual effects on the target, thus providing valuable insight into the mechanisms responsible for the problem. The Source-Path-Receiver concept is used. The sources can be from the road surface, engine, transmission, transfer case, prop-shaft, differential, rotating components, chain drives, pumps, etc., and the receiver can be driver/passenger ears, steering column, seats, etc. This paper is devoted to identify the noise transfer paths and the force transmissibility among the interfaces of different components in the vehicle for the low to mid frequency range.

A generalized re-normalization group (RNG) turbulence model based on the local "dimensionality" of the flow field is proposed. In this modeling approach the model coefficients C₁, C₂, and C₃ are all constructed as functions of flow strain rate. In order to further validate the proposed turbulence model, the generalized RNG closure model was applied to model the backward facing step flow (a classic test case for turbulence models). The results indicated that the modeling of C₂ in the generalized RNG closure model is reasonable, and furthermore, the predictions of the generalized RNG model were in better agreement with experimental data than the standard RNG turbulence model. As a second step, the performance of the generalized RNG closure was investigated for a complex engine flow.

The paper presents the development of a novel approach to the solution of detailed chemistry in internal combustion engine simulations, which relies on the analytical computation of the ordinary differential equations (ODE) system Jacobian matrix in sparse form. Arbitrary reaction behaviors in either Arrhenius, third-body or fall-off formulations can be considered, and thermodynamic gas-phase mixture properties are evaluated according to the well-established 7-coefficient JANAF polynomial form. The current work presents a full validation of the new chemistry solver when coupled to the KIVA-4 code, through modeling of a single cylinder Caterpillar 3401 heavy-duty engine, running in two-stage combustion mode.

A lumped electro-thermal model for a battery module with 14 cells in series (14S1P), and with a cooling channel, is created by two-way coupling of an equivalent circuit model (ECM) and a linear time-invariant (LTI) method based thermal reduced order model (ROM). To create the ROM, a step response data in the form of temperature versus time curve is required. This data is obtained by running a transient full three-dimensional (3D) computational fluid dynamics (CFD) analysis for the full module. The thermal ROM accounts for the effect of the heat generated by the active cells, the joule heat generated in tabs and connectors, and the coolant inlet temperature. To create an ECM, data from hybrid pulse power characterization (HPPC) test is used. Such a lumped electro-thermal model for a battery module can run faster than a 3D CFD analysis and can be easily integrated in a system level model.

The comfort assessment of seats in the automotive industry has historically been accomplished by subjective ratings. This approach is expensive and time consuming since it involves multiple prototype seats and numerous people in supporting processes. In order to create a more efficient and robust method, objective metrics must be developed and utilized to establish measurable boundaries for seat performance. Objective measurements already widely accepted, such as IFD (Indentation Force Deflection) or CFD (Compression Force Deflection) [1], have significant shortcomings in defining seat comfort. The most obvious deficiency of these component level tests is that they only deal with a seats' foam rather than the system response. Consequently, these tests fail to take into account significant factors that affect seat comfort such as trim, suspension, attachments and other components.

This paper reviews the engine modeling program in the Powertrain Control Research Laboratory at the University of Wisconsin-Madison, focuses on simulation results obtained from a complete modular turbocharged diesel engine dynamic model developed in this lab, and suggests ways that dynamic engine system models can be used in the design process. It examines the dynamic responses and interactions between various components in the engine system, looks at how these components affect the overall performance of the system in transient and steady state operation.

Digital human models (DHM) are now widely used to assess worker tasks as part of manufacturing simulation. With current DHM software, the simulation engineer or ergonomist usually makes a manual estimate of the likely worker standing location with respect to the work task. In a small number of cases, the worker standing location is determined through physical testing with one or a few workers. Motion capture technology is sometimes used to aid in quantitative analysis of the resulting posture. Previous research has demonstrated the sensitivity of work task assessment using DHM to the accuracy of the posture prediction. This paper expands on that work by demonstrating the need for a method and model to accurately predict worker standing location. The effect of standing location on work task posture and the resulting assessment is documented through three case studies using the Siemens Jack DHM software.

Fundamental understanding of the sources of fuel-derived Unburned Hydrocarbon (UHC) emissions in heavy duty diesel engines is a key piece of knowledge that impacts engine combustion system development. Current emissions regulations for hydrocarbons can be difficult to meet in-cylinder and thus after treatment technologies such as oxidation catalysts are typically used, which can be costly. In this work, Computational Fluid Dynamics (CFD) simulations are combined with engine experiments in an effort to build an understanding of hydrocarbon sources. In the experiments, the combustion system design was varied through injector style, injector rate shape, combustion chamber geometry, and calibration, to study the impact on UHC emissions from mixing-controlled diesel combustion.

In this paper, a low-cost means to improve fuel economy in conventional vehicles by employing ultracapacitor based Active Energy Recovery Buffer (AERB) scheme will be presented. The kinetic energy of the vehicle during the coast down events is utilized to charge the ultracapacitor either directly or through a dc-dc converter, allowing the voltage to increase up to the maximum permissible level. When the vehicle starts after a Stop event, the energy stored in the capacitor is discharged to power the accessory loads until the capacitor voltage falls below a minimum threshold. The use of stored capacitor energy to power the accessory loads relieves the generator torque load on the engine resulting in reduced fuel consumption. Two different topologies are considered for implementing the AERB system. The first topology, which is a simple add-on to the conventional vehicle electrical system, comprises of the ultracapacitor bank and the dc-dc converter connected across the dc bus.

Trivial Principal Component method (TPC) was developed recently to model a system based on measured data. It is a statistical method that utilizes Eigen-pairs of covariance matrix obtained from the measured data. It determines linear coefficients of a model by using the trivial eigenvector corresponding to the least eigenvalue. In general, linear modeling accuracy depends on the strength of nonlinearity and interaction terms as well as measurement error. In this paper, the TPC method is extended to analyze residual (error) vector to identify significant higher order and interaction terms that contribute to the modeling error. Subsequently, these additional terms are included for constructing a robust system model. Also, an iterative TPC analysis is proposed for the first time to correct the model gradually till the least eigenvalue becomes minimum.

Automobile drivers/passengers perceive automatic transmission (AT) shift quality through the torque transferred by the transmission. Clearly, torque regulation is important for transmission control. Unfortunately, a physical torque sensor has been too costly for production applications. With no torque measurement for feedback, controls in AT is mainly implemented in an open-loop fashion. Therefore, complicated adaptation algorithms are necessary while undesired shifts may still occur. To further simplify the controls and enhance its consistency and robustness, a direct torque feedback has long been desired in transmission control synthesis and development. A “virtual” torque sensor (VTS) algorithm has recently been developed to show a good potential in estimating relative torque along transmission output shaft using transmission output speed sensor and wheel speed sensors.

This paper presents a response to the question: Simulation - mathematical manipulation or useful design tool? A mathematical model of a modulating valve in a transmission control system was developed to predict clutch pressure modulation characteristics. The transmission control system was previously reported in SAE Paper 850783 - “Electronic/Hydraulic Transmission Control System for Off-Highway Vehicles”. The comparison of simulation predictions with test data illustrates the effectiveness of simulation as a design tool. THE EVOLUTION OF COMPUTER hardware and simulation software has resulted in increased interest and usage of simulation for dynamic analysis of hydraulic systems. Most commercially available software is relatively easy to learn to use. The application of such software and the modeling techniques involved require a longer learning curve.

Due to the multitude of external design constraints, such as increasing fuel economy standards, and the increasing number of global vehicle programs, developers of automotive transmission controls have had to cope with increasing levels of system complexity while at the same time being forced by the marketplace to improve system quality, reduce development costs, and improve time to market. General Motors Powertrain (GMPT) chose to meet these challenges through General Motors Company's Road-to-Lab-to-Math (RLM) strategy, particularly the Math-based method of a virtual vehicle simulation environment called System Simulation. The use of System Simulation to develop transmission control algorithms has enabled GMPT to improve product quality and reduce development times and costs associated with the dependence on physical prototypes. Additionally, System Simulation has facilitated the reuse of GMPT controls development assets, improving overall controls development efficiency.

This paper reports on a comprehensive, crank-angle transient, three dimensional, computational fluid dynamics (CFD) model of the complete lubrication system of a multi-cylinder engine using the CFD software Simerics-Sys / PumpLinx. This work represents an advance in system-level modeling of the engine lubrication system over the current state of the art of one-dimensional models. The model was applied to a 16 cylinder, reciprocating internal combustion engine lubrication system. The computational domain includes the positive displacement gear pump, the pressure regulation valve, bearings, piston pins, piston cooling jets, the oil cooler, the oil filter etc… The motion of the regulation valve was predicted by strongly coupling a rigorous force balance on the valve to the flow.

Traffic state identification is a key problem in intelligent transportation system. As a new technology, connected and automated vehicle can play a role of identifying traffic state with the installation of onboard sensors. However, research of lane level traffic state identification is relatively lacked. Identifying lane level traffic state is helpful to lane selection in the process of driving and trajectory planning. In addition, traffic state identification precision with low penetration of connected and automated vehicles is relatively low. To fill this gap, this paper proposes a novel method of identifying traffic state in the presence of connected and automated vehicles with low penetration rate. Assuming connected and automated vehicles can obtain information of surrounding vehicles’, we use the perceptible information to estimate imperceptible information, then traffic state of road section can be inferred.

The development of analytic models of diesel engine flow, combustion and subprocesses is described. The models are intended for use as design tools by industry for the prediction of engine performance and emissions to help reduce engine development time and costs. Part of the research program includes performing engine experiments to provide validation data for the models. The experiments are performed on a single-cylinder version of the Caterpillar 3406 engine that is equipped with state-of-the-art high pressure electronic fuel injection and emissions instrumentation. In-cylinder gas velocity and gas temperature measurements have also been made to characterize the flows in the engine.

In recent years, there has been a sustained effort by the automotive OEMs and suppliers to improve the vehicle driveline efficiency. This has been in response to customer demands for greater vehicle fuel economy and increasingly stringent government regulations. The automotive rear axle is one of the major sources of power loss in the driveline, and hence represents an area where power loss improvements can have a significant impact on overall vehicle fuel economy. Both the friction induced mechanical losses and the spin losses vary significantly with the operating temperature of the lubricant. Also, the preloads in the bearings can vary due to temperature fluctuations. The temperatures of the lubricant, the gear tooth contacting surfaces, and the bearing contact surfaces are critical to the overall axle performance in terms of power losses, fatigue life, and wear.