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Advanced High Strength Steels (AHSS) have been implemented in the automotive industry to balance the requirements for vehicle crash safety, emissions, and fuel economy. With lower ductility compared to conventional steels, the fracture behavior of AHSS components has to be considered in vehicle crash simulations to achieve a reliable crashworthiness prediction. Without considering the fracture behavior, component fracture cannot be predicted and subsequently the crash energy absorbed by the fractured component can be over-estimated. In full vehicle simulations, failure to predict component fracture sometimes leads to less predicted intrusion. In this paper, the feasibility of using computer simulations in predicting fracture during crash deformation is studied.

A wet clutch model is required in automotive propulsion system simulations for enabling robust design and control development. It commonly assumes Coulomb friction for simplicity, even though it does not represent the physics of hydrodynamic torque transfer. In practice, the Coulomb friction coefficient is treated as a tuning parameter in simulations to match vehicle data for targeted conditions. The simulations tend to deviate from actual behaviors for different drive conditions unless the friction coefficient is adjusted repeatedly. Alternatively, a complex hydrodynamic model, coupled with a surface contact model, is utilized to enhance the fidelity of system simulations for broader conditions. The theory of elastic asperity deformation is conventionally employed to model clutch surface contact. However, recent examination of friction material shows that the elastic modulus of surface fibers significantly exceeds the contact load, implying no deformation of fibers.

The introduction of carbon fiber reinforced polymer (CFRP) composites to structural components in lightweight automotive structures necessitates an assessment to evaluate that their crashworthiness dynamic response provides similar or higher levels of safety compared to conventional metallic structures. In order to develop, integrate and implement predictive computational models for CFRP composites that link the materials design, molding process and final performance requirements to enable optimal design and manufacturing vehicle systems for this study, the dynamic mechanical response of unidirectional (UD) and 2x2 twill weave CRFP composites was characterized at deformation rates applicable to crashworthiness performance. Non-standardized specimen geometries were tested on a standard uniaxial frame and an intermediate-to-high speed dynamic testing frame, equipped with high speed cameras for 3D digital image correlation (DIC).

Three computational gas and fluid dynamic methods, CV/UP (Control Volume/Uniform Pressure), CPM (Corpuscular Particle Method), and ALE (Arbitrary Lagrangian and Eulerian), were investigated in this research in an attempt to predict the responses of side crash pressure sensors. Acceleration-based crash sensors have been used extensively in the automotive industry to determine the restraint system firing time in the event of a vehicle crash. The prediction of acceleration-based crash pulses by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crush zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side crash applications.

Air quenching is a common manufacturing process in automotive industry to produce high strength metal component by cooling heated parts rapidly in a short period of time. With the advancement of finite element analysis (FEA) methods, it has been possible to predict thermal residual stress by computer simulation. Previous research has shown that heat transfer coefficient (HTC) for steady air quenching process is time and temperature independent but strongly flow and geometry dependent. These findings lead to the development of enhanced HTC method by performing CFD simulation and extracting HTC information from flow field. The HTC obtained in this fashion is a continuous function over the entire surface. In current part of the research, two patching algorithms are developed to divide entire surface into patches according to HTC profile and each patch is assigned a discrete HTC value.

This paper focuses on finding and analyzing the relevant parameters affecting traffic flow when autonomous vehicles are introduced for ride hailing applications and autonomous shuttles are introduced for circulator applications in geo-fenced urban areas. For this purpose, different scenarios have been created in traffic simulation software that model the different levels of autonomy, traffic density, routes, and other traffic elements. Similarly, software that specializes in vehicle dynamics, physical limitations, and vehicle control has been used to closely simulate realistic autonomous vehicle behavior under such scenarios. Different simulation tools for realistic autonomous vehicle simulation and traffic simulation have been merged together in this paper, creating a realistic simulator with Hardware-in-the-Loop (HiL), Traffic-in-the-Loop (TiL), and Software in-the-Loop (SiL) simulation capabilities.

Self-piercing rivets (SPR) are efficient and economical joining methods used in the manufacturing of lightweight automotive bodies. The finite element method (FEM) is a potentially effective way to assess the joining process of SPRs. However, uncertain parameters could lead to significant mismatches between the FEM predictions and physical tests. Thus, a sensitivity study on critical model parameters is important to guide the high-fidelity modeling of the SPR insertion process. In this paper, an axisymmetric FEM model is constructed to simulate the insertion process of the SPR using LS-DYNA/explicit. Then, several surrogate models are evaluated and trained using machine learning methods to represent the relations between selected inputs (e.g., material properties, interfacial frictions, and clamping force) and outputs (cross-section dimensions).

A step-ratio automatic transmission alters torque paths for gearshifting through engagement and disengagement of clutches. It enables torque sources to run efficiently while meeting driver demand. Yet, clutch thermal energy during gearshifting is one of the contributors to the overall fuel loss. In order to optimize drivetrain control strategy, including the frequency of shifts, it is important to understand the cost of shift itself. In a power-on upshift, clutch thermal energy is primarily dissipated during inertia phase. The interaction between multiple clutches, coupled with input torque truncation, makes the decomposition of overall energy loss less obvious. This paper systematically presents the mathematical analysis of clutch thermal energy during the inertia phase of a typical single-transition gearshift. In practice, a quicker shift is generally favored, partly because the amount of energy loss is considered smaller.

In the automobile industry, the reliability and predictive capabilities of computer models for a dynamic system need to be assessed quantitatively. Quantitative validation allows engineers to assess and improve model reliability and quality objectively and ultimately lead to potential reduction in the number of prototypes built and tests. A good metric, which is essential in model validation, requires considering uncertainties in both testing and computer modeling. In addition, it needs to be able to compare multiple responses simultaneously, as multiple quantities are often encountered at different spatial and temporal points of a dynamic system. In this paper, a state-of-the-art validation technology is developed for multivariate complex dynamic systems by exploiting a probabilistic principal component analysis method and Bayesian statistics approach.

Notched spoilers may be used to suppress flow-induced cavity resonance in vehicles with open sunroofs or side windows. The notches are believed to generate streamwise vortices that break down the structure of the leading edge cross-stream vortices predominantly responsible for the cavity excitation. The objectives of the present study were to gain a better understanding of the buffeting suppression mechanisms associated with notched spoilers, and to gather data for computational model verification. To this end, experiments were performed to characterize the surface pressure field downstream of straight and notched spoilers mounted on a rigid wall to observe the effects of the notches on the static and dynamic wall pressure. Detailed flow velocity measurements were made using hot-wire anemometry. The results indicated that the presence of notches on the spoiler reduces drag, and thus tends to move the flow reattachment location closer to the spoiler.

Powertrain Engineering Tool (PET) [1, 2, 3], developed at Ford Powertrain and Vehicle Research Laboratory, is a powertrain computer model that allows rapid development of preliminary powertrain component geometry, and evaluation of engine performance and friction. Based on specified design objectives such as engine torque, power and geometric constraints, PET calculates the powertrain component geometry by employing its integrated design rules and a non-linear SQP-based (Sequential Quadratic Programming) geometry optimizer. PET also generates parametric solid models of powertrain systems based on its integrated dynamic component assembly schemes and solid modeling database. The cranktrain system consists of high-speed moving and rotating components. Complex dynamic analysis is typically required to achieve optimum cranktrain component design. This paper discusses development of a systematic approach in the calculation of optimal cranktrain component geometry.

Detailed computer models of system components for More Electric Aircraft have been developed using the Advanced Control System Language (ACSL) and its graphical front-end, Graphic Modeller. Among the devices modeled are a wound-rotor synchronous generator with parallel bridge-rectifier outputs, a switched-reluctance generator, and various loads including a DC-DC converter, an inverter-driven induction motor, and an electro-hydrostatic actuator. Results from the simulations are presented together with corroborating experimental test results.

The method of multiple reference frames is employed in the development of a state variable model for brushless DC drives with non-sinusoidal back emf waveforms. This model has the desirable features of being valid for transient and steady-state analysis as well as having state variables that are constant in the steady-state. The model facilitates both nonlinear and linear system analysis and control design. Computer simulation and experimental data are included to validate the analysis.

Advances in digital and analog electronics have drastically changed car radio circuitry. Improvements in miniaturization of electrical and mechanical components have radically altered their size and styling. Computer modeling of the vehicle's interior environment has optimized car radio acoustics. It seems that the list of modern break-throughs is never ending. It is the intent of this paper to show that many of the technical marvels of today's car radios were first applied years, even decades, ago. From those early concepts, and their current revivals, a projection into the future of automobile radios will be made. As previously mentioned [1]: “If history teaches anything, it teaches the potential for repetition.”

A computational model of a mid-size sport utility vehicle was developed using MADYMO. The model includes a detailed description of the suspension system and tire characteristics that incorporated the Delft-Tyre magic formula description. The model was correlated by simulating a vehicle suspension kinematics and compliance test. The correlated model was then used to simulate a J-turn vehicle dynamics test maneuver, a roll and non-roll ditch test, corkscrew ramp and a lateral trip test, the results of which are presented in this paper. The results indicate that MADYMO is able to reasonably predict the vehicle and occupant responses in these types of applications and is potentially suited as a tool to help setup a suite of vehicle configurations and test conditions for rollover sensor testing. A suspension system sensitivity study is presented for the laterally tripped non-roll event.

Macroscopic constitutive behaviors of aluminum 5052-H38 honeycombs under dynamic inclined loads with respect to the out-of-plane direction are investigated by experiments. The results of the dynamic crush tests indicate that as the impact velocity increases, the normal crush strength increases and the shear strength remains nearly the same for a fixed ratio of the normal to shear displacement rate. The experimental results suggest that the macroscopic yield surface of the honeycomb specimens as a function of the impact velocity under the given dynamic inclined loads is not governed by the isotropic hardening rule of the classical plasticity theory. As the impact velocity increases, the shape of the macroscopic yield surface changes, or more specifically, the curvature of the yield surface increases near the pure compression state.

A track-type grapple log skidder was dynamically modeled to allow machine modification by computer to determine the effects of these modifications on the operation of the machine in the forest. The model consisted of an undercarriage, power train, log/drag force, and logging equipment (arch and grapple). This skidder had three types of logging attachments: winch, swinging boom (grapple), and single-function arch (grapple). Each was modeled and simulated under various conditions. The dynamic model of the skidder can be used to analyze its drawbar pull capability and lateral stability with various log weights and soil types on steep slopes. Validation of this model is needed later.

Due to complexities of interaction among gears and crescent-shaped island, a crescent oil pump is one of the most difficult auto components to model using three dimensional Computational Fluid Dynamics(CFD) method. This paper will present a novel approach to address the challenges inherent in crescent oil pump modeling. The new approach is incorporated into the commercial pump design tool PumpLinx from Simerics, Inc.. The new method is applied to simulate a production crescent oil pump with inlet/outlet ports, inner/outer gears, irregular shaped crescent island and tip leakages. The pump performance curve, cavitation effects and pressure ripples are studied using this tool and will be presented in this paper. The results from the simulations are compared to the experiment data with excellent agreement. The present study shows that the proposed computational model is very accurate and robust and can be used as a reliable crescent pump design tool.

Computer Aided Engineering (CAE) has become a vital tool for product development in automotive industry. Various computer models for occupant restraint systems are developed. The models simulate the vehicle interior, restraint system, and occupants in different crash scenarios. In order to improve the efficiency during the product development process, the model quality and its predictive capabilities must be ensured. In this research, an objective model validation metric is developed to evaluate the model validity and its predictive capabilities when multiple occupant injury responses are simultaneously compared with test curves. This validation metric is based on the probabilistic principal component analysis method and Bayesian statistics approach for multivariate model assessment. It first quantifies the uncertainties in both test and simulation results, extracts key features, and then evaluates the model quality.

Grunt is a structure-born noise caused by resonance of the steering gear torsion bar (T-bar) in an HPAS (Hydraulic Power Assist Steering) system. The goal of this work was to develop techniques to quantify and predict grunt in a RV (rotary valve) steering gear system. First, vehicle testing was used to identify an objective metric for grunt: y = dynamic pressure in the return line. Then, a computer simulation was developed to predict y as a function of two known control factors. The simulation results were correlated to measurements on a test vehicle. Finally, the simulation was expanded to include two additional control factors, and grunt predictions were demonstrated on a different test vehicle.