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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.

The development and calibration of stress state-dependent failure criteria for advanced high-strength steel (AHSS) and aluminum alloys requires characterization under proportional loading conditions. Traditional tests to construct a forming limit diagram (FLD), such as Marciniak or Nakazima tests, are based upon identifying the onset of strain localization or a tensile instability (neck). However, the onset of localization is strongly dependent on the through-thickness strain gradient that can delay or suppress the formation of a tensile instability so that cracking may occur before localization. As a result, the material fracture limit becomes the effective forming limit in deformation modes with severe through-thickness strain gradients, and this is not considered in the traditional FLD. In this study, a novel bending test apparatus was developed based upon the VDA 238-100 specification to characterize fracture in plane strain bending using digital image correlation (DIC).

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).

This paper intends to present a novel optimal trajectory planning method for obstacle avoidance on highways. Firstly, a mapping from the road Cartesian coordinate system to the road Frenet-based coordinate system is built, and the path lateral offset in the road Frenet-based coordinate system is represented by a function of quintic polynomial respecting the traveled distance along the road centerline. With different terminal conditions regarding its position, heading and curvature of the endpoint, and together with initial conditions of the starting point, the path planner generates a bunch of candidate paths via solving nonlinear equation sets numerically. A path selecting mechanism is further built which considers a normalized weighted sum of the path length, curvature, consistency with the previous path, as well as the road hazard risk.

The driver's face detection and tracking method important for Advanced Driver Assistance Systems (ADAS) and autonomous driving in various situations. The deep SORT algorithm has integrated appearance information, the motion model and the intersection-over-union (IOU) distance methods, and has been applied to face tracking, but it depends on detection information in every frame. Once the detection information lacks, the deep SORT algorithm will wait until the target detects bounding boxes appear again, even if the target didn’t disappear or shield. Hence, we propose to use a new tracker that not completely depend on the detection algorithm to cascade with the deep SORT algorithm to realize stable driver's face tracking. At first, the driver's face detection and tracking will be accomplished by the MTCNN-deep-SORT algorithm.

The vision for the future automotive chassis is to interconnect the lateral, longitudinal, and vertical dynamics by separately controlling driving, braking, steering, and damping of each individual wheel. A major advantage of all wheel drive electric vehicles with four in-wheel motors is the possibility to control the torque and speed at each wheel independently. This paper proposes a traction controller for such a vehicle. It estimates the road's adhesion potential at each wheel and adjusts each motor voltage, such that the longitudinal slip is kept in an optimal range. For development and validation, a full vehicle model is designed in ADAMS/View software, in co-simulation with motor and control elements, modeled in MATLAB/Simulink.

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.

The conversion design strategy, and emissions and performance results for a dedicated propane, vapour injected, 1995 Dodge Dakota truck are reported. Data is obtained from the University of Waterloo entry in the 1997 Propane Vehicle Challenge. A key feature of the design strategy is its focus on testing and emissions while preserving low engine speed power for drivability. Major changes to the Dakota truck included the following: installation of a custom shaped fuel tank, inclusion of a fuel temperature control module, addition of a vaporizer and a fuel delivery metering unit, installation of a custom vapour distribution manifold, addition of an equivalence ratio electronic controller, inclusion of a wide range oxygen sensor, addition of an exhaust gas recirculation cooler and installation of thermal insulation on the exhaust system. A competition provided natural gas catalyst was used.

A fuel cell hybrid powertrain design is implemented and optimized by the University of Waterloo Alternative Fuels Team for the ChallengeX competition. A comprehensive set of bench-top and in-vehicle validation results are used to generate accurate fuel cell vehicle models for SIL/HIL control strategy testing and tuning. The vehicle is brought to a “99% buy-off” level of production readiness, and a detailed crashworthiness analysis is performed. The vehicle performance is compared to Vehicle Technical Specifications (VTS).

Traditional electrode materials for lithium-ion storage cells are typically crystalline layered structures such as metal oxides, and graphitic carbons. These materials power billions of portable electronic devices in today's society. However, large-scale, high-capacity storage devices capable of powering hybrid electric vehicles (HEV″s) or their plug-in versions (PHEV's) have much more demanding requirements with respect to safety, cost, and the power they must deliver. Recently, nanostructured solid state materials, which are comprised of two more compositional or structural phases, have been found to show exciting possibilities to meet these criteria.

Ride performance characteristics of a road vehicle involving different suspension system layouts are investigated. The suspension layouts consist of conventional rectangular 4-wheel, novel diamond-shaped 4-wheel, triangular 3-wheel and inverse-triangular 3-wheel. A generalized full-vehicle model integrating different suspension system layouts is formulated. The fundamental suspension properties are compared in terms of bounce-, roll- and pitch-mode. The ride dynamic responses and power consumption characteristics are explored under two measured road roughness excitations and a range of vehicle speeds. The results demonstrate that the novel diamond-shaped suspension system layout could yield significantly enhanced vehicle ride performance in an energy-saving manner.

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.

Stretch flange features are commonly found in the corner regions of commercial parts, such as window cutouts, where large strains can induce localization and necking. In this study, laboratory-scale stretch flange forming experiments on AA5182 and AA5754 were conducted to address the formability of these aluminum alloys under undergoing this specific deformation process. Two distinct cracking modes were found in the stretch flange samples. One is radial cracking at the inner edge of flange (cutout edge) while the other is circumferential cracking away from the inner edge at the punch profile radius. Numerical simulation of the stretch flange forming operations was conducted with an explicit finite element code-LS-DYNA. A coalescence-suppressed Gurson-based material model is used in the finite element model. Void coalescence and final failure in stretch flange is simulated through measured second-phase particle fields with a so-called damage percolation model.

Electromagnetic forming of aluminum alloys provides improved forming limits, minimal springback and rapid implementation. The ability to predict the minimum energy required in electromagnetic forming is essential in developing an efficient process. Understanding the development of the strain distribution over time in the blank is also highly desired. A numerical model is needed that offers insight into these areas and the electromagnetic forming process in general that cannot easily be extracted from experiments. To address these concerns, ANSYS/EMAG is used to model the time varying currents that are discharged through the coil in order to obtain the transient magnetic forces acting on the blank. The body forces caused by electromagnetic induction are then used as the boundary condition to model the high velocity deformation of the blank with LS-DYNA, an explicit dynamic finite element code.

This paper investigates the application of standard formability testing results for aluminum alloy tailor welded blanks (TWB) to full size stampings. The limit strains obtained from formability testing are compared to measured strains in a larger scale part. The measured strains in the full scale part are also compared to predictions from finite element simulation.

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.