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Hole expansion of a dual phase steel, DP600, was numerically investigated using a damage-based constitutive law to predict failure. The parameters governing void nucleation and coalescence were identified from an extensive review of the x-ray micro-tomography data available in the literature to ensure physically-sound predictions of damage evolution. A recently proposed technique to experimentally quantify work-hardening and damage in the shear-affected zone is incorporated into the damage model to enable fracture predictions of holes with sheared edges. Finite-element simulations of a hole expansion test with a conical punch were performed for both a punched and milled hole edge condition and the predicted hole expansion ratios are in very good agreement with the experiment values reported by several researchers.

Small crack growth from notches under variable amplitude loading requires that crack opening stress be followed on a cycle by cycle basis and taken into account in making fatigue life predictions. The use of constant amplitude fatigue life data that ignores changes in crack opening stress due to high stress overloads in variable amplitude fatigue leads to non-conservative fatigue life predictions. Similarly fatigue life predictions based on small crack growth calculations for cracks growing from flaws in notches are non-conservative when constant amplitude crack growth data are used. These non-conservative predictions have, in both cases, been shown to be due to severe reductions in fatigue crack closure arising from large (overload or underload) cycles in a typical service load history.

A control algorithm is developed for active/semi-active suspensions which can provide more comfort and better handling simultaneously. A weighting parameter is tuned online which is derived from two components - slow and fast adaptation to assign weights to comfort and handling. After establishing through simulations that the proposed adaptive control algorithm can demonstrate a performance better than some controllers in prior-art, it is implemented on an actual vehicle (Cadillac STS) which is equipped with MR dampers and several sensors. The vehicle is tested on smooth and rough roads and over speed bumps.

The analysis of nickel metal hydride (Ni-MH) battery performance is very important for automotive researchers and manufacturers. The performance of a battery can be described as a direct consequence of various chemical and physical phenomena taking place inside the container. In this paper, a physics-based model of a Ni-MH battery will be presented. To analyze its performance, the efficiency of the battery is chosen as the performance measure, which is defined as the ratio of the energy output from the battery and the energy input to the battery while charging. Parametric sensitivity analysis will be used to generate sensitivity information for the state variables of the model. The generated information will be used to showcase how sensitivity information can be used to identify unique model behavior and how it can be used to optimize the capacity of the battery. The results will be validated using a finite difference formulation.

The performance, life cycle cost, and safety of electric and hybrid electric vehicles (EVs and HEVs) depend strongly on their energy storage system. Advanced batteries such as lithium-ion (Li-ion) polymer batteries are quite viable options for storing energy in EVs and HEVs. In addition, thermal management is essential for achieving the desired performance and life cycle from a particular battery. Therefore, to design a thermal management system, a designer must study the thermal characteristics of batteries. The thermal characteristics that are needed include the surface temperature distribution, heat flux, and the heat generation from batteries under various charge/discharge profiles. Therefore, in the first part of the research, surface temperature distribution from a lithium-ion pouch cell (20Ah capacity) is studied under different discharge rates of 1C, 2C, 3C, and 4C.

In this paper, a consensus framework for cooperative parameter estimation within the vehicular network is presented. It is assumed that each vehicle is equipped with a dedicated short range communication (DSRC) device and connected to other vehicles. The improvement achieved by the consensus for parameter estimation in presence of sensor’s noise is studied, and the effects of network nodes and edges on the consensus performance is discussed. Finally, the simulation results of the introduced cooperative estimation algorithm for estimation of the unknown parameter of road condition is presented. It is shown that due to the faster dynamic of network communication, single agents’ estimation converges to the least square approximation of the unknown parameter properly.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

System identification is an important aspect in model-based control design which is proven to be a cost-effective and time saving approach to improve the performance of hybrid electric vehicles (HEVs). This study focuses on modeling and parameter estimation of the longitudinal vehicle dynamics for Toyota Prius Plug-in Hybrid (PHEV) with power-split architecture. This model is needed to develop and evaluate various controllers, such as energy management system, adaptive cruise control, traction and driveline oscillation control. Particular emphasis is given to the driveline oscillations caused due to low damping present in PHEVs by incorporating flexibility in the half shaft and time lag in the tire model.

Forecasting the motion of the leading vehicle is a critical task for connected autonomous vehicles as it provides an efficient way to model the leading-following vehicle behavior and analyze the interactions. In this study, a personalized time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The method enables a precise, personalized trajectory prediction for leading vehicles with limited inter-vehicle communication signals, such as vehicle speed, acceleration, space headway, and time headway of the front vehicles. Based on the learning nature of human beings that a human always tries to solve problems based on grouping and similar experience, three different driving styles are first recognized based on an unsupervised clustering with a Gaussian Mixture Model (GMM).

Significant improvement in fuel consumption, torque delivery and emission could be achieved through flexible control of the valve timings, duration and lift. In most existing electro-hydraulic variable valve actuation systems, the desired valve lift within every engine cycle is achieved by accurately controlling of the solenoid-valve opening interval; however, due to slow response time, precision control of these valves is difficult particularly during higher engine speeds. In this paper a new lift control strategy is proposed based on the hydraulic supply pressure and flow control. In this method, in order to control the peak valve lift, the hydraulic pump speed is precisely controlled using a two-input gearbox mechanism. This eliminates the need for precision control of the solenoid valves opening interval within every cycle.

This paper presents the numerical validation of the impact response of a hot formed B-pillar component with tailored properties. A laboratory-scale B-pillar tool is considered with integral heating and cooling sections in an effort to locally control the cooling rate of an austenitized blank, thereby producing a part with tailored microstructures to potentially improve the impact response of these components. An instrumented falling-weight drop tower was used to impact the lab-scale B-pillars in a modified 3-point bend configuration to assess the difference between a component in the fully hardened (martensitic) state and a component with a tailored region (consisting of bainite and ferrite). Numerical models were developed using LS-DYNA to simulate the forming and thermal history of the part to estimate the final thickness and strain distributions as well as the predicted microstructures.

It is imperative to have accurate tire models when trying to control the trajectory of a vehicle. With the emergence of autonomous vehicles, it is more important than ever before to have models that predict how the vehicle will operate in any situation. Many different types of tire models have been developed and validated, including physics-based models such as brush models, black box models, finite element-based models, and empirical models driven by data such as the Magic Formula model. The latter is widely acknowledged to be one of the most accurate tire models available; however, collecting data for this model is not an easy task. Collecting data is often accomplished through rigorous testing in a dedicated facility. This is a long and expensive procedure which generally destroys many tires before a comprehensive data set is acquired. Using a Vehicle Measurement System (VMS), tires can be modeled through on-road data alone.

In this study, a finite element software application (SORPAS®) is used to simulate the effect of pulsing on the expected weld thermal cycle during resistance spot welding (RSW). The predicted local cooling rates are used in combination with experimental observation to study the effect pulsing has on the microstructure and mechanical properties of Zn-coated DP600 AHSS (1.2mm thick) spot welds. Experimental observation of the weld microstructure was obtained by metallographic procedures and mechanical properties were determined by tensile shear testing. Microstructural changes in the weld metal and heat affect zone (HAZ) were characterized with respect to process parameters.

Motorized shoulder belt tensioning is an occupant protection technology that has promise to reduce automotive crash injuries. The objective of this study was to model the response of a diverse forward-leaning occupant population (6-year-old child, 5th female, 50th male, 95th male) to shoulder belt tensioning during straight line pre-crash braking. The lumped mass model was based on experimental volunteer data for motorized shoulder belt tensioning gathered in a previous quasistatic study. The three dimensional model incorporated the biomechanical properties of the occupant populations, a motorized shoulder belt tensioner (DC motor and controller) and shoulder belt webbing models. Model validation was achieved against the volunteer experiments for angular torso position, torso velocity and shoulder belt moment applied to the torso.

Porous silicon as gas/chemical sensing material has been widely investigated in recent years. In this paper, the humidity sensing property of n-type porous silicon with ordered structure is studied for the first time. The ordered porous silicon used in this experiment has uniform pore size, pore shape and distribution. Both the membrane and closed bottom samples were studied. The resistance change of the porous silicon was measured. A 22-28% decrease of resistance was observed when relative humidity was changed from 1% to 100%. Both the response time and the recovery time were within 10 minutes, and 90% of the response can be reached in 6 minutes for the PS membrane sample. The possible sensing mechanism and future work are also discussed in this paper.

In this work, a new air hybrid engine is introduced in which two throttles are used to manage the engine load in three modes of operation i.e. braking, air motor, and conventional mode. The concept includes an air tank to store pressurized air during braking and rather than a fully variable valve timing (VVT) system, two throttles are utilized. Use of throttles can significantly reduce the complexity of air hybrid engines. The valves need three fixed timing schedules for the three modes of operation. To study this concept, for each mode, the results of engine simulations using GT-Power software are used to generate the operating maps. These maps show the maximum braking torque as well as maximum air motor torque in terms of air tank pressure and engine speed. Moreover, the resulting maps indicate the operating conditions under which each mode is more effective. Based on these maps, a power management strategy is developed to achieve improved fuel economy.

Vehicles designed for the Baja SAE competition operate on challenging off-road terrain and may be required to withstand accidental impacts with other vehicles and obstacles. Although significant injuries are not commonly observed in this competition, it is important to understand the performance of these vehicles in crash scenarios to optimize frame design and vehicle performance. A finite element model comprising the vehicle chassis and associated subsystem weights, a Hybrid III occupant, and safety systems was developed to evaluate vehicle impact performance in frontal crash. Impacts velocities up to 36 kph were considered, and no significant risk of head, neck or thoracic injury was predicted. Neck injury (as predicted by Nij) and chest acceleration were found to be the most critical, reaching 66% and 75% of their threshold values, respectively, in the most severe crashes considered.

This paper examines the application of damage models in tube bending and subsequent hydroforming of AlMg3.5Mn aluminum alloy tubes. An in-house Gurson-based damage model, incorporated within LS-DYNA, has been used for the simulations. The applied damage model contains several void nucleation and growth parameters that must be determined for each material. A simpler straight tube hydroforming process was considered first to check the damage parameters and predicted ductility. Then the model was applied to a sequence of bending and hydroforming. The damage history from pre-bending was mapped to the hydroforming stage, to allow prediction of the overall ductility. The applied forming parameters in the simulation were based on data extracted during the experimental tests. Finally, the numerical results were compared to the experimental data.

A so-called damage percolation model is coupled with Gurson-based finite element (FE) approach in order to accommodate the high strain gradients and localized ductile damage. In doing so, void coalescence and final failure are suppressed in Gurson-based FE modeling while a measured second phase particle field is mapped onto the most damaged mesh area so that percolation modeling can be performed to capture ductile fracture in real sheet forming operations. It is revealed that void nucleation within particle clusters dominates ductile fracture in aluminum alloy sheet forming. Coalescence among several particle clusters triggered final failure of materials. A stretch flange forming is simulated with the coupled modeling.

The present work investigates weld failure modes during formability tests of multi-gauge aluminum Tailor Welded Blanks (TWBs). The limiting dome height test is used to evaluate formability of TWBs. Three gauge combinations utilizing aluminum alloy 5754 sheets are considered (2 to 1 mm, 1.6 to 1 mm and 2 to 1.6 mm). Three weld orientations have been considered: transverse, longitudinal and 45°. Interaction of several factors determines the type of failure that occurs in a TWB specimen. These factors are weld orientation, morphology and distribution of weld defects, and the magnitude of constraint imposed by the thicker sheet to the thin sheet. The last factor depends on the difference in thickness of the sheet pair and is usually expressed in terms of gauge ratio. In general TWBs show two different types of fracture: weld failure and failure of the thin aluminum sheet. Only the former will be discussed in this paper.