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As mass reduction becomes an increasingly important enabler for fuel economy improvement, having a robust structural development process that can comprehend Vehicle Dynamics-specific requirements is correspondingly important. There is a correlation between the stiffness of the body structure and the performance of the vehicle when evaluated for ride and handling. However, an unconstrained approach to body stiffening will result in an overly-massive body structure. In this paper, the authors employ loads generated from simulation of quasi-static and dynamic vehicle events in ADAMS, and exercise structural finite element models to recover displacements and deflected shapes. In doing so, a quantitative basis for considering structural vehicle dynamics requirements can be established early in the design/development process.

Polyvinyl Butyral (PVB) laminated glass has been widely used in automotive industry as windshield material. Cracks on the PVB laminated glass contain large amount of impact information, which can contribute to accident reconstruction investigation. In this study, the impact-induced in-plane dynamic cracking of the PVB laminated glass is investigated. Firstly, a drop-weight combined with high-speed photography experiment device is set up to investigate the radial cracks propagation on the PVB laminated glass sheet. Both the morphology and the velocity time history curve of the radial cracks are recorded and analyzed to investigate the basic mechanism of the crack propagation process. Afterwards, a three-dimensional laminated plate finite element (FE) model is set up and dynamic cracking process is simulated based on the extended finite element method (XFEM).

Detailed chemical kinetics is essential for accurate prediction of combustion performance as well as emissions in practical combustion engines. However, implementation of that is challenging. In this work, dynamic adaptive chemistry (DAC) is integrated into large eddy simulations (LES) of an n-heptane spray flame in a constant volume chamber (CVC) with realistic application conditions. DAC accelerates the time integration of the governing ordinary differential equations (ODEs) for chemical kinetics through the use of locally (spatially and temporally) valid skeletal mechanisms. Instantaneous flame structures and global combustion characteristics such as ignition delay time, flame lift-off length (LOL) and emissions are investigated to assess the effect of DAC on LES-DAC results. The study reveals that in LES-DAC simulations, the auto-ignition time and LOL obtain a well agreement with experiment data under different oxygen concentrations.

Modelling of disc in brake squeal analysis is complicated because of the rotation of disc and the sliding contact between disc and pads. Many analytical or analytical numerical combined modeling methods have been developed considering the disc brake vibration and squeal as a moving load problem. Yet in the most common used complex eigenvalue analysis method, the moving load nature normally has been ignored. In this paper, a new modelling method for rotating disc from the point of view of modal is presented. First finite element model of stationary disc is built and modal parameters are calculated. Then the dynamic response of rotating disc which is excited and observed at spatial fixed positions is studied. The frequency response function is derived through space and time transformations. The equivalent modal parameter is extracted and expressed as the function of rotation speed and original stationary status modal parameters.

The study and prevention of unstable vibration is a challenging task for vehicle industry. Improving predicting accuracy of braking squeal model is of great concern. Closed-loop coupling disc brake model is widely used in complex eigenvalue analysis and further analysis. The coupling stiffness of disc rotor and pads is one of the most important parameters in the model. But in most studies the stiffness is calculated by simple static force-deformation simulation. In this paper, a closed-loop coupling disc brake model is built. Initial values of coupling stiffness are estimated from static calculation. Experiment modal analysis of stationary disc brake system with brake line pressure and brake torques applied is conducted. Then an optimization process is initiated to minimize the differences between modal frequencies predicted by the stationary model and those from test. Thus model parameters more close to reality are found.

A computational fluid dynamics (CFD) guided design optimization was conducted for the piston bowl geometry for a heavy-duty diesel engine. The optimization goal was to minimize engine-out NOx emissions without sacrificing engine peak power and thermal efficiency. The CFD model was validated with experiments and the combustion system optimization was conducted under three selected operating conditions representing low speed, maximum torque, and rated power. A hundred piston bowl shapes were generated, of which 32 shapes with 3 spray angles for each shape were numerically analyzed and one optimized design of piston bowl geometry with spray angle was selected. On average, the optimized combustion system decreased nitrogen oxide (NOx) emissions by 17% and soot emissions by 41% without compromising maximum engine power and fuel economy.

The performance of electric vehicles could be enhanced by more flexible drivetrain configurations combined with advanced control methods. Based on four wheel independent driving and front and rear axle modular steering configuration, which was proposed by our research group last year, the problem of slippery under close-to-limit conditions are further discussed and simulated. A new torque vectoring method based on obtainable parameters and variables in real driving situations is introduced to reduce the sideslip when turning on low friction surfaces or with high speed. This method is developed from a comprehensive index, which reflects the stability and maneuverability, by adding additional torques when stability could not be compensated enough by basic torque vectoring. Besides, an improvement of adding a simu-Torsen differential mechanism is made to the model of the vehicle, which enables another control method with the same purpose as before.

General Motors has developed an all-new Ecotec 1.5 L range extender engine for use in the 2016 next generation Voltec propulsion system. This engine is part of a new Ecotec family of small displacement gasoline engines introduced in the 2015 model year. Major enhancements over the range extender engine in the current generation Voltec propulsion system include the adoption of direct injection (DI), cooled external exhaust gas recirculation (EGR), and a high 12.5:1 geometric compression ratio (CR). Additional enhancements include the adoption of high-authority phasers on both the intake and exhaust camshafts, and an integrated exhaust manifold (IEM). The combination of DI with cooled EGR has enabled significant thermal efficiency gains over the 1.4 L range extender engine in the current generation Voltec propulsion system at high engine loads.

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.

This article is concerned with identification of true stress-strain curve under biaxial tension of thermoplastic polymers. A new type of biaxial tension attachment was embedded first in a universal material test machine, which is able to transform unidirectional loading of the test machine to biaxial loading on the specimen with constant velocity. Cruciform specimen geometry was optimized via FE modeling. Three methods of calculating true stress in biaxial tension tests were compared, based on incompressibility assumption, linear elastic theory and inverse engineering method, respectively. The inverse engineering method is more appropriate for thermoplastic polymers since it considers the practical volume change of the material during biaxial tension deformation. The strategy of data processing was established to obtain biaxial tension true stress-strain curves of different thermoplastic polymers.

Traffic congestions are increasingly severe in urban areas, especially at the merging areas of the ramps and the arterial roads. Because of the complex conflict relationship of the vehicles in ramps and arterial roads in terms of time-spatial constraints, it is challenging to coordinate the motion of these vehicles, which may easily cause congestions at the merging areas. The connected and automated vehicles (CAVs) provides potential opportunities to solve this problem. A centralized merging control method for CAVs is proposed in this paper, which can organize the traffic movements in merging areas efficiently and safely. In this method, the merging control model is built to formulate the vehicle coordination problem in merging areas, which is then transformed to the discrete nonlinear optimization form. A simulation model is built to verify the proposed method.

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).

Lane-changing systems have been developed and applied to improve environmental adaptability of advanced driver assistant system (ADAS) and driver comfort. Lane-changing control consists of three steps: decision making, trajectory planning and trajectory tracking. Current methods are not perfect due to weaknesses such as high computation cost, low robustness to uncertainties, etc. In this paper, a novel lane changing control method is proposed, where lane-changing behavior is analogized to parallel parking behavior. In the perspective of host vehicle with lane-changing intention, the space between vehicles in the target adjacent lane can be regarded as dynamic parking space. A decision making and path planning algorithm of parallel parking is adapted to deal with lane change condition. The adopted algorithm based on rules checks lane-changing feasibility and generates desired path in the moving reference system at the same speed of vehicles in target lane.

Studying drifting dynamics and control could extend the usable state-space beyond handling limits and maximize the potential safety benefits of autonomous vehicles. Distributed electric vehicles provide more possibilities for drifting control with better grip and larger maximum drift angle. Under the state of drifting, the distributed electric vehicle is a typical nonlinear over-actuated system with actuator redundancy, and the coupling of input vectors impedes the direct use of control algorithm of upper. This paper proposes a novel automated drifting controller for the distributed electric vehicle. First, the nonlinear over-actuated system, comprised of driving system, braking system and steering system, is formulated and transformed to a square system through proposed integrative recombination method of control channel, making general nonlinear control algorithms suitable for this system.

In low-temperature environment, heat supply requires considerable energy, which significantly increases energy consumption and shortens the mileage of electric vehicle. In the fuel cell vehicles, waste heat generated by the fuel cell system can supply heat for vehicle. In this paper, a thermal management system is designed for a the fuel cell interurban bus. Thermal management strategy aiming at temperature regulation for the fuel cell stack and the passenger compartment and minimal energy consumption is proposed. System model is developed and simulated based on AMESim and Matlab/Simulink co-simulation. Simulation results show that the fuel cell system can provide about 78 % energy of maximum heat requirement in -20 °C ambient temperature environment.

Compressed natural gas (CNG) currently is used as an alternative fuel for internal combustion engines in motor vehicles. This paper presents results of an analysis of leaks from a model isolated section of CNG fuel system. Discharge of CNG was modeled as vent flow of a real gas hydrocarbon mixture through an orifice from a reservoir with finite volume. Pressures typically used in CNG fuel systems result in choked flow for gas venting directly to atmosphere, producing an under-expanded, momentum-dominated, turbulent free jet with well defined velocity and concentration fields. This paper presents results of analyses of reservoir pressure decay, and vent flow and concentrations fields for CNG venting from a pressurized reservoir into the atmosphere. A combination of empirically-derived analytical relationships and detailed two-dimensional high resolution computational fluid dynamic modeling was used to determine the velocity and concentrations fields of the resulting CNG jet.

A comprehensive experimental and theoretical approach was undertaken to understand the phenomenon of pre-ignition and to assess parameters to improve or even eliminate it completely. Oil mixing with fuel was identified as the leading theory of self ignition of the fuel. End of compression temperature has to meet a minimum level for pre-ignition to take place. In this work a comprehensive list of parameters were identified that have a direct and crucial role in the onset of pre-ignition including liner wetting, injection targeting, stratification, mixture motion and oil formulation. Many secondary effects were identified including ring dynamics, ring tension, spark plug electrode temperature and coolant temperature. CFD has been extensively used to understand test results including wall film, A/F ratio distribution and temperature at the end of compression when looked at in the context of fuel evaporation and mixing.

As the new features for driver assistance and active safety systems are growing rapidly in vehicles, the simulation within a virtual environment has become a necessity. The current active safety system consists of Electronic Control Units (ECUs) which are coupled to camera and radar sensors. Two methods of implementation exists, integrated sensors with control modules or separation of sensors form control modules. The subsystem integration testing poses new challenges for virtual environment for simulation of active safety features. The comprehensive simulation environment for integration testing consists of chassis controls, powertrain, driver assistance, body and displays controllers. Additional complexity in the system is the serial communication strategy. Multiple communication protocols such as GMLAN, LIN, standard CAN, and Flexray could be present within the same vehicle topology.

Three different acoustic finite element models of an automobile passenger compartment are developed and experimentally assessed. The three different models are a traditional model, an improved model, and an optimized model. The traditional model represents the passenger and trunk compartment cavities and the coupling between them through the rear seat cavity. The improved model includes traditional acoustic models of the passenger and trunk compartments, as well as equivalent-acoustic finite element models of the front and rear seats, parcel shelf, door volumes, instrument panel, and trunk wheel well volume. An optimized version of the improved acoustic model is developed by modifying the equivalent-acoustic properties. Modal analysis tests of a vehicle were conducted using loudspeaker excitation to identify the compartment cavity modes and sound pressure response to 500 Hz to assess the accuracy of the acoustic models.

At elevated temperatures, such as those encountered under race track or fade test conditions, the closed-form solution to the lumped capacitance model for characterizing brake cooling (fitted to a standard cooling test temperature range) tends to break down and provide an inaccurate representation of brake rotor cooling behavior. Accurate prediction of cooling is fundamental to brake system component sizing and selection of materials at the early stages of a vehicle program; this is especially true of a high performance vehicle with track performance requirements. To this end, alternative approaches to characterizing brake cooling have been examined to determine their suitability for use in measurement and simulation of brake performance.