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Dynamic modelling of the contact between the tires of automobiles and the road surface is crucial for accurate and effective vehicle dynamic simulation and the development of various driving controllers. Furthermore, an accurate prediction of the rolling resistance is needed for powertrain controllers and controllers designed to reduce fuel consumption and engine emissions. Existing models of tires include physics-based analytical models, finite element based models, black box models, and data driven empirical models. The main issue with these approaches is that none of these models offer the balance between accuracy of simulation and computational cost that is required for the model-based development cycle. To address this issue, we present a volumetric approach to model the forces/moments between the tire and the road for vehicle dynamic simulations.

The present work is aimed at investigating the tribological factors influencing the LDH test. The material used was AKDQ cold-rolled bare steel, 0.82mm thick. The investigated factors included: test speed (0.833, 4.167, 6.667, and 8.333 mm/s), lubricant viscosity (4.5, 7.0, and 12.5 mm2/s), punch roughness (0.033 and 0.144 μm Ra), and test temperature (25 and 50 °C). Test speed and lubricant viscosity form a variation of the numerator of the Stribeck curve's x-axis (ηV). With ηV increasing from 4 to 120 mm3/s2 friction decreased, resulting in a 0.5 mm higher LDH. Increasing the punch roughness decreased friction producing an increase of 0.25 mm in the LDH. There appears to be an optimum roughness -- at which the roughness features act as lubricant reservoirs but the asperities do not break through the lubricant film -- resulting in minimum friction, therefore, maximum LDH.

Details of the development of metal transfer and friction were studied by drawing cold-rolled bare, galvannealed, electrogalvanized, and hot-dip galvanized strips with a mineral-oil lubricant of 30 cSt viscosity at 40 C, over a total distance of 2500 mm by three methods. An initial high friction peak was associated with metal transfer to the beads and was largest with pure zinc and smallest with Fe-Zn coatings. Insertion of a new strip disturbed the coating and led to the development of secondary peaks. Long-term trends were governed by the stability of the coating. Stearic acid added to mineral oil delayed stabilization of the coating and increased contact area and thus friction with pure zinc surfaces. The usual practice of reporting average friction values can hide valuable information on lubrication mechanisms and metal transfer.

A series plug-in hybrid electric powertrain with all-wheel drive is designed using real-world drive cycles as part of the EcoCAR 2 competition. A stock 2013 Chevrolet Malibu Eco is being re-engineered to reduce fuel consumption and emissions while improving consumer acceptability. Waterloo utilizes a 18.9 kWh A123 energy storage system (ESS), which powers two 105 kW TM4 traction motors. A 2.4 L LE9 General Motors coupled to a 105 kW TM4 motor provides range extending performance. Each step of the design process is discussed, including a novel approach to powertrain selection and controls requirement selection that uses real-world drive cycles. The mechanical integration and unique ESS design is also discussed.

The objective of this paper is to help students optimize project component selection or design by detailing, through two specific examples, the University of Waterloo's Alternative Fuels Team's (UWAFT's) successful design process. UWAFT successfully designed a fuel cell powered vehicle for the ChallengeX student engineering competition. The use of a formal, structured design process enabled this team to achieve great confidence in both the feasibility of their design and their ability to manifest the design. This design process is model-based whereby a parameterized software model is created. This paper hopefully assists students to overcome a common reluctance to implementing a model-based design process. After a component is constructed and tested, students can update their software model, which can help them assess the strength of their design.

The present paper offers a status report on round-robin tests conducted with the participation of ten laboratories, with drawbead simulation (DBS) as the test method. The results showed that, in most laboratories, the coefficient of friction (COF) derived from the test is repeatable within an acceptable range of ±0.01. Repeatability between laboratories was less satisfactory. Five laboratories reported results within the desirable band, while some laboratories found consistently higher values. In one instance this could be traced to incomplete transfer of clamp forces to the load cell, in other instances inaccurate test geometry is suspected. Therefore, numerical values of COF from different laboratories are not necessarily comparable. Irrespective of these inter-laboratory variations, the relative ranking of lubricants was not affected, and data generated within one laboratory can be used for relative evaluations and for a resolution of production problems.

This paper seeks to identify the refrigeration load of a hybrid electric truck in order to find the demand power required by the energy management system. To meet this objective, in addition to the power consumption of the refrigerator, the vehicle mass needs to be estimated. The Recursive Least Squares (RLS) method with forgetting factors is applied for this estimation. As an example of the application of this parameter identification, the estimated parameters are fed to the energy control strategy of a parallel hybrid truck. The control system calculates the demand power at each instant based on estimated parameters. Then, it decides how much power should be provided by available energy sources to minimize the total energy consumption. The simulation results show that the parameter identification can estimate the vehicle mass and refrigeration load very well which is led to have fairly accurate power demand prediction.

Recently, the development of braking assistance system has largely benefit the safety of both driver and pedestrians. A robust prediction and detection of driver braking intention will enable driving assistance system response to traffic situation correctly and improve the driving experience of intelligent vehicles. In this paper, two types unsupervised clustering methods are used to build a driver braking intention predictor. Unsupervised machine learning algorithms has been widely used in clustering and pattern mining in previous researches. The proposed unsupervised learning algorithms can accurately recognize the braking maneuver based on vehicle data captured with CAN bus. The braking maneuver along with other driving maneuvers such as normal driving will be clustered and the results from different algorithms which are K-means and Gaussian mixture model (GMM) will be compared.

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.

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.

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.

The autoignition delay of a turbulent methane jet in a Diesel-like environment is calculated by the conditional moment closure(CMC) model. Methane is injected into hot air in a constant volume chamber under various temperatures and pressures. Detailed chemical reaction mechanisms are implemented with turbulence-chemistry interaction treated by the first order CMC. The CMC model solves the conditional mean species mass fraction and temperature equations with the source term given in terms of the conditional mean quantities. The flow and mixing field are calculated by the transient SIMPLE algorithm with the k -ε model and the assumed beta function pdf. The CMC equations are solved by the fractional step method which sequentially treats the transport and chemical reaction terms in each time step. The predictions in quiescent homogeneous mixture are presented to evaluate the effects of turbulence in jet ignition.

Vehicle weight reduction through the use of components made of magnesium alloys is an effective way to reduce carbon dioxide emission and improve fuel economy. In the design of these components, which are mostly under cyclic loading, notches are inevitably present. In this study, surface strain distribution and crack initiation sites in the notch region of AZ31B-H24 magnesium alloy notched specimens under uniaxial load are measured via digital image correlation. Predicted strains from finite element analysis using Abaqus and LS-DYNA material types 124 and 233 are then compared against the experimental measurements during quasi-static and cyclic loading. It is concluded that MAT_233, when calibrated using cyclic tensile and compressive stress-strain curves, is capable of predicting strain at the notch root. Finally, employing Smith-Watson-Topper model together with MAT_233 results, fatigue lives of the notched specimens are estimated and compared with experimental results.

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.

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.

Direct injected natural gas diesel engines are currently being developed. Numerical analyses results are presented for 20.0 MPa (≈ 3000 psia; 200 atm), 444 K, natural gas injection into 4.0 MPa cylinder air where the ambient turbulence field is representative of diesel engines. Two very important non-intuitive, observations are made. First, the seemingly reasonable spatially uniform velocity profile currently used at the injector exit is not appropriate, rather a double-hump profile is correct. Second, a spatially uniform, injector exit, temperature profile results in local temperature overestimates as large as 300 K. Considering the strong role of temperature on chemical kinetics, this second observation may have profound implications on the validity of conclusions reached using uniform exit profiles.

Hybrid electric vehicles (HEVs) are considered as the most commercial prospects new energy vehicles. Most HEVs have adopted Atkinson cycle engine as the main drive power. Atkinson cycle engine uses late intake valve closing (LIVC) to reduce pumping losses and compression work in part load operation. It can transform more heat energy to mechanical energy, improve engine thermal efficiency and decrease fuel consumption. In this paper, the investigations of Atkinson cycle converted from conventional Otto cycle gasoline engine have been carried out. First of all, high geometry compression ratio (CR) has been optimized through piston redesign from 10.5 to 13 in order to overcome the intrinsic drawback of Atkinson cycle in that combustion performance deteriorates due to the decline in the effective CR. Then, both intake and exhaust cam profile have been redesigned to meet the requirements of Atkinson cycle engine.

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 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).

Proton exchange membrane fuel cell (PEMFC) is considered to be one of the best clean power sources for transportation application. Water management is a critical issue, conventionally achieved by coating the cell components with the hydrophobic materials. In this work, the effects of one surface-coated cathode gas diffusion layer (GDL) on water removal rate, droplet dynamics, and the cell performance have been studied. The coated GDL is fabricated by coating one side of raw GDL (SpectraCarb 2050-A) with 15 wt. % of polytetrafluoroethylene (PTFE) solution but the other side remains uncoated. The raw GDL is commercial one and made of carbon fiber. The contact angles (θ) on both sides of the coated and raw GDL are measured. The pore size distribution, and capillary pressure are measured for the GDL, studied using the method of standard porosimetry (MSP). Water removal rate is measured by using a 20 ml syringe barrel, wherein a 13 mm diameter GDL token is stuck on the barrel opening.