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Existing gasoline DI injection equipment has been modified to generate single hole pulsed gas jets. Injection experiments have been performed at combinations of 3 different pressure ratios (2 of which supercritical) respectively 3 different hole geometries (i.e. length to diameter ratios). Injection was into a pressure chamber with optical access. Injection pressures and injector hole geometry were selected to be representative of current and near-future DI natural gas engines. Each injector hole design has been characterized by measuring its discharge coefficient for different Re-levels. Transient jets produced by these injectors have been visualized using planar laser sheet Mie scattering (PLMS). For this the injected gas was seeded with small oil droplets. The corresponding flow field was measured using particle image velocimetry (PIV) laser diagnostics.

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.

This paper discusses the development and subsequent validation process of generic multi-body models for commercial vehicle combinations. The model is intended for performance assessment and improving of current and future combinations for the European road network. A second goal is to employ the model for the development of driver support systems and active steering strategies for both low speed manoeuvrability and high speed stability. The model is developed in SimMechanics, which is part of the MATLAB/Simulink software. Due to its modularity, one can quickly modify the model to the desired configuration and dimensions; therefore various multi articulation vehicle models can be created. The paper further illustrates the simplified and generic modelling methods used to build particular components such as chassis, tyres or suspension in the multibody domain.

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.

Energy management strategies greatly influence the power performance and fuel economy of series hybrid electric tracked bulldozers. In this paper, we present a procedure for the design of a power management strategy by defining a cost function, in this case, the minimization of the vehicle’s fuel consumption over a driving cycle. To explore the fuel-saving potential of a series hybrid electric tracked bulldozer, a dynamic programming (DP) algorithm is utilized to determine the optimal control actions for a series hybrid powertrain, and this can be the benchmark for the assessment of other control strategies. The results from comparing the DP strategy and the rule-based control strategy indicate that this procedure results in approximately a 7% improvement in fuel economy.

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.

The modeling of fuel sprays under well-characterized conditions relevant for heavy-duty Diesel engine applications, allows for detailed analyses of individual phenomena aimed at improving emission formation and fuel consumption. However, the complexity of a reacting fuel spray under heavy-duty conditions currently prohibits direct simulation. Using a systematic approach, we extrapolate available spray models to the desired conditions without inclusion of chemical reactions. For validation, experimental techniques are utilized to characterize inert sprays of n-dodecane in a high-pressure, high-temperature (900 K) constant volume vessel with full optical access. The liquid fuel spray is studied using high-speed diffused back-illumination for conditions with different densities (22.8 and 40 kg/m3) and injection pressures (150, 80 and 160 MPa), using a 0.205-mm orifice diameter nozzle.

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).

Diesel spray mixture formation is investigated at target conditions using multiple diagnostics and laboratories. High-speed Particle Image Velocimetry (PIV) is used to measure the velocity field inside and outside the jet simultaneously with a new frame straddling synchronization scheme. The PIV measurements are carried out in the Engine Combustion Network Spray A target conditions, enabling direct comparisons with mixture fraction measurements previously performed in the same conditions, and forming a unique database at diesel conditions. A 1D spray model, based upon mass and momentum exchange between axial control volumes and near-Gaussian velocity and mixture fraction profiles is evaluated against the data.

A computationally efficient engine model is developed based on an extended NO emission model and state-of-the-art soot model. The model predicts exhaust NO and soot emission for both conventional and advanced, high-EGR (up to 50 %), heavy-duty DI diesel combustion. Modeling activities have aimed at limiting the computational effort while maintaining a sound physical/chemical basis. The main inputs to the model are the fuel injection rate profile, in-cylinder pressure data and trapped in-cylinder conditions together with basic fuel spray information. Obtaining accurate values for these inputs is part of the model validation process which is thoroughly described. Modeling results are compared with single-cylinder as well as multi-cylinder heavy-duty diesel engine data. NO and soot level predictions show good agreement with measurement data for conventional and high-EGR combustion with conventional timing.

Torque converters are used as coupling devices in automobile powertrains involving automatic transmissions. Efficient modeling of torque converters capturing various modes of operation is important for powertrain design and simulation, (Hroval and Tobler 1, Ishihara and Emori 2) optimization and control applications. Models of torque converters are available in various commercial simulation packages, Hadi et. al. 3. The information about the effect of model parameters on torque converter performance is valuable for any design operation. In this paper, a symbolic sensitivity analysis of a torque converter model will be presented. Direct differentiation (Serban and Freeman 4) is used to generate the sensitivity equations which results in equations in symbolic form. By solving the sensitivity equations, the effect of a perturbation of the model parameters on the behavior of the system is determined.

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.

At Eindhoven University of Technology an active suspension system has been developed [1]. This system is superior to other active suspension in terms of bandwidth and power consumption. This active suspension system was tested on a quarter car setup and showed improvements of up to 48% in comfort [2]. In order to implement this suspension in a test vehicle with the same improvements, a non-linear full-car model is developed in this paper which is used to simulate and design various controllers. The non-linear model incorporates non-linear damping, bump stops, actuator saturation and actuator friction. To model the friction in the actuator a combination of Coulomb and viscous friction is used. To model the MacPherson suspension strut, two methods are described and compared. Also the implications of using acceleration sensors which are placed in line with the MacPherson strut are discussed.

Residual stress prediction arising from manufacturing processes provides paramount information for the fatigue performance assessment of components subjected to cyclic loading. The determination of the material model to be applied in the numerical model should be taken carefully. This study focuses on the estimation of residual stresses generated after deep rolling of cast iron crankshafts. The researched literature on the field employs the available commercial material codes without closer consideration on their reverse loading capacities. To mitigate this gap, a single element model was used to compare potential material models with tensile-compression experiments. The best fit model was then applied to a previously developed crankshaft deep rolling numerical model. In order to confront the simulation outcomes, residual stresses were measured in two directions on real crankshaft specimens that passed through the same modeled deep rolling process.

A predictive model of a specific vehicle was modeled in the system-level physical modeling tool, MapleSim, for performance and fuel consumption prediction of a full vehicle powertrain, driving a multi-body chassis model with tire models. The project also includes investigation into overall fuel efficiency and effect on vehicle handling for different drive cycles. The goals of this project were to investigate: 1) the relationships between the forces at tire/road interfaces during various drive cycles and the fuel efficiency of a vehicle, and 2) the interaction between the powertrain and the chassis of the vehicle. To accomplish these goals, a complete vehicle model was created in the lumped-parameter physical modeling tool, MapleSim. A great deal of effort has gone into using real parameters and to assure that some mathematical rigour has been employed in its development.

Owing to environmental and health concerns, tetraethyl lead was gradually phased out from the early 1970's to mid-1990's in most developed countries. Advances in refining, leading to more aromatics (via reformate) and iso-paraffins such as iso-octane, along with the introduction of (bio) oxygenates such as MTBE, ETBE and ethanol, facilitated the removal of lead without sacrificing RON and MON. In recent years, however, legislation has been moving in the direction of curbing aromatic and olefin content in gasoline, owing to similar concerns as was the case for lead. Meanwhile, concerns over global warming and energy security have motivated research into renewable fuels. Amongst which are those derived from biomass. The feedstock of interest in this study is lignin, which, together with hemicellulose and cellulose, is amongst the most abundant organic compounds on the planet.

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.

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.