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A method to improve the computational efficiency of analyzing wheeled vehicle systems on three-dimensional (3-D) roads has been developed. This was accomplished by creating a technique to incorporate the tire on a 3-D road in a multibody dynamics model of the vehicle with an approach that formulates the governing equations using symbolic formulation. For general handling analysis performed on the vehicle, the tire forces and moments are determined using a tire model that represents the tire as a set of mathematical expressions. Since these expressions need numerical values to determine the forces and moments, a symbolic solution does not exist. Therefore, the evaluation of the tire forces and moments needs to be done during simulation. However, symbolic operations can be used when the governing equations are formulated to develop an efficient method to evaluate these forces.

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.

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 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).

In vehicles equipped with conventional Electric Power Steering (EPS) systems, the steering effort felt by the driver can be unreasonably low when driving on slippery roads. This may lead inexperienced drivers to steer more than what is required in a turn and risk losing control of the vehicle. Thus, it is sensible for tire-road friction to be accounted for in the design of future EPS systems. This paper describes the design of an auxiliary EPS controller that manipulates torque delivery of current EPS systems by supplying its motor with a compensation current controlled by a fuzzy logic algorithm that considers tire-road friction among other factors. Moreover, a steering system model, a nonlinear vehicle dynamics model and a Dugoff tire model are developed in MATLAB/Simulink. Physical testing is conducted to validate the virtual model and confirm that steering torque decreases considerably on low friction roads.

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.

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 presents a road classifier based on the system response with consideration of the tire enveloping. The aim is to provide an easily applicable yet accurate road classification approach for automotive engineers. For this purpose, tire enveloping effect is firstly modeled based on the flexible roller contact (FRC) theory, then transfer functions between road input and commonly used suspension responses i.e. the sprung mass acceleration, unsprung mass acceleration, and rattle space, are calculated for a quarter vehicle model. The influence of parameter variations, vehicle velocity, and measurement noise on transfer functions are comprehensively analyzed to derive the most suitable system response thereafter. In addition, this paper proposes a vehicle speed correction mechanism to further improve the classification accuracy under complex driving conditions.

A compact sized vehicle that has a narrow track could solve problems caused by vehicle congestion and limited parking spaces in a mega city. Having a smaller footprint reduces the vehicle's total weight which would decrease overall vehicle power consumption. Also a smaller and narrower vehicle could travel easily through tight and congested roads that would speed up the traffic flow and hence decrease the overall traffic volume in urban areas. As an additional benefit of having a narrow track length, a driver can experience similar motorcycle riding experience without worrying about bad weather conditions since a driver sits in a weather protected cabin. However, reducing the vehicle's track causes instability in vehicle dynamics, which leads to higher possibility of rollovers if the vehicle is not controlled properly. A three wheel personal vehicle with an active tilting system is designed in MapleSim.

A rapid inexpensive evaluation and comparison of the cyclic properties of three steels used in the automotive industry is presented. This evaluation ranges from the endurance limit through the transition life and low cycle regions to the monotonic results. Smooth and notched specimens, tested in strain control and load control, respectively, provide data that are used to indicate notch sensitivity and size effects, cyclic strength and ductility, and cyclic deformation response. The effect of overloads on fatigue damage is given and prestrained smooth specimens demonstrate the possible effect of a few large plastic strain cycles on fatigue resistance. Overloaded notched specimens indicate reductions in life due to both large plastic strain cycles and the induced tensile residual stress. These data are suitable for direct insertion into the design process and also provide a broad base for continuing studies of cyclic behavior.

This paper presents an optimal cooperative path planning method considering driver’s driving intention for shared control to address target path conflicts during the driver-automation interaction by using the convex optimization technique based on the natural cubic spline. The optimal path criteria (e.g. the optimal curvature, the optimal heading angle) are formulated as quadratic forms using the natural cubic spline, and the initial cooperative path profiles of the cooperative path in the Frenet-based coordinate system are induced by considering the driver’s lane-changing intention recognized by the Support Vector Machine (SVM) method. Then, the optimal cooperative path could be obtained by the convex optimization techniques. The noncooperative game theory is adopted to model the driver-automation interaction in this shared control framework, where the Nash equilibrium solution is derived by the model predictive control (MPC) approach.

Plane strain tension is the critical stress state for sheet metal forming because it represents the extremum of the yield function and minima of the forming limit curve and fracture locus. Despite its important role, the stress response in plane strain deformation is routinely overlooked in the calibration of anisotropic plasticity models due to challenges and uncertainty in its characterization. Plane strain tension test specimens used for constitutive characterization typically employ large gage width-to-thickness ratios to promote a homogeneous plane strain stress state. Unfortunately, the specimens are limited to small strain levels due to fracture initiating at the edges in uniaxial tension. In contrast, notched plane strain tension coupons designed for fracture characterization have become common in the automotive industry to calibrate stress-state dependent fracture models. These coupons have significant stress and strain gradients across the gage width to avoid edge fracture.

The effect of stress triaxiality on failure strain in as-cast magnesium alloy AM60B is examined. Experiments using one uniaxial and two notched tensile geometries were used to study the effect of stress triaxiality on the quasi-static constitutive response of super vacuum die cast AM60B castings. For all tests, local strains, failure location and specimen elongation were tracked using two-dimensional digital image correlation (DIC) analysis. The uniaxial specimens were tested in two orthogonal directions to determine the anisotropy of the casting. Finite element models were developed to estimate effective plastic strain histories and stress state (triaxiality) as a function of notch severity. It was found that there is minimal, if any, anisotropy present in AM60B castings. Higher stress triaxiality levels caused increases in maximum stress and decreases in elongation and local effective plastic strain at failure.

Using standard tensile testing methods, the material properties of AKDQ and DP600 steels tubes along the axial direction were determined. A novel in-situ optical strain mapping system ARAMIS® was utilized to evaluate the strain distribution during tensile testing along the axial direction. Microstructural and damage characterization was carried out using microscopy and image analysis techniques to compare the damage evolution and formability of both materials. Failure in both steels was observed to occur via a ductile failure mode. AKDQ was found to be the more formable material as it can achieve higher strains, total elongations and thinning prior to failure than the higher strength DP600.

With the widespread development of automated driving systems (ADS), it is imperative that standardized testing methodologies be developed to assure safety and functionality. Scenario testing evaluates the behavior of an ADS-equipped subject vehicle (SV) in predefined driving scenarios. This paper compares four modes of performing such tests: closed-course testing with real actors, closed-course testing with surrogate actors, simulation testing, and closed-course testing with mixed reality. In a collaboration between the Waterloo Intelligent Systems Engineering (WISE) Lab and AAA, six automated driving scenario tests were executed on a closed course, in simulation, and in mixed reality. These tests involved the University of Waterloo’s automated vehicle, dubbed the “UW Moose”, as the SV, as well as pedestrians, other vehicles, and road debris.

The superior formability and local ductility of the emerging class of third generation of advanced high-strength steels (3rd Gen AHSS) compared to their conventional counterparts of the same strength level offer significant advantages for automotive lightweighting and enhanced crash performance. Nevertheless, studies on the material behavior of 3rd Gen AHSS have been limited and there is some uncertainty surrounding the applicability of developed methodologies for conventional dual-phase (DP) steels to this new class of AHSS. The present paper provides a comprehensive study on the quasi-static and dynamic constitutive behavior, formability characterization and prediction, and the fracture behavior of two commercial 3rd Gen AHSS with an ultimate strength of 1180 MPa that will be contrasted with a conventional DP1180. The hardening response to large strain levels was determined experimentally using tensile and shear tests and then validated with 3-D simulations of tensile tests.

Accurately predicting the future trajectories of surrounding traffic agents is important for ensuring the safety of autonomous vehicles. To address the scenario of frequent interactions among traffic agents in the highway merging area, this paper proposes a trajectory prediction method based on interactive graph attention mechanism. Our approach integrates an interactive graph model to capture the complex interactions among traffic agents as well as the interactions between these agents and the contextual map of the highway merging area. By leveraging this interactive graph model, we establish an agent-agent interactive graph and an agent-map interactive graph. Moreover, we employ Graph Attention Network (GAT) to extract spatial interactions among trajectories, enhancing our predictions. To capture temporal dependencies within trajectories, we employ a Transformer-based multi-head self-attention mechanism.

Modern electrified vehicles rely on drivers to manually adjust control parameters to modify the vehicle's powertrain, such as regenerative braking strength selection or drive mode selection. However, this reliance on infrequent driver input may lead to a mismatch between the selected powertrain control modifiers and the true driving environment. It is therefore advantageous for an electric vehicle's powertrain controller to make online identifications of the current driving conditions. This paper proposes an online driving condition identification scheme that labels drive cycle intervals collected in real-time based on a clustering model, with the objective of informing adaptive powertrain control strategies. HDBSCAN and K-means clustering models are fitted to a data set of drive cycle intervals representing a full range of characteristic driving conditions.

1 Crack initiation and propagation test data gathered during tests on Keyhole notched samples is used to evaluate a fatigue life prediction technique. Materials tested include a lower strength ManTen steel and a higher strength Boron steel, RQC-100, both tested with constant and variable amplitude histories. Initiation fatigue life is predicted using the usual method of plasticity correction at the notch followed by a Palmgren-Miner summation of damage with mean stress correction. The emphasis of the study is on simulating the crack propagation results. For that phase discretetize da/dN vs ΔK lines and thresholds for negative R ratios, are used specifically to help predict the propagation for one of the VA histories that had a significant negative mean. The open source crack propagation simulation program applies a material memory model to determine the crack advance on a reversal by reversal basis.