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A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An integral part of this System is an Intervention Strategy that uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. Through this strategy, the driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models. This work develops one means to alter the future vehicle states: modulating the driver's brake commands. This control strategy must be considered in relationship to changes in the throttle commands. Three key elements of this strategy are developed in this work.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models which is the focus of this work. This work develops one means to alter the future vehicle states: modulating the driver's throttle commands. First, changes to the longitudinal force are translated to changes in engine torque based on the current operating state (torque and speed) of the engine.

Magnetic Resonance Velocimetry (MRV) measurements are performed in 1:1 scale models of a single-cylinder optical engine to investigate the differences in the inlet flow due to geometrical changes of the cylinder head. The models are steady flow water-analogue of the optical IC engine with a fixed valve lift of 9.21 mm to simulate the induction flow at 270° bTDC. The applicability of MRV to engine flows despite the differences in experimental operating parameters between the steady flow model and the optical IC engine are demonstrated and well addressed in this manuscript and in a previous work [1]. To provide trust into the MRV measurements, the data is validated with phase-averaged particle image velocimetry (PIV) measurements performed within the optical engine. The main geometrical changes between the cylinder heads include a variation of intake valve diameter and slight modifications to the exit of the intake port.

Particle image velocimetry measurements of the in-cylinder flow in an optically accessible single-cylinder research engine were taken to better understand the effects of intake pressure variations on the flow field. At a speed of 1500 rpm, the engine was run at six different intake pressure loads from 0.4 to 0.95 bar under motored operation. The average velocity fields show that the tumble center position is located closer to the piston and velocity magnitudes decrease with increasing pressure load. A closer investigation of the intake flow near the valves reveals sharp temporal gradients and differences in maximum and minimum velocity with varying intake pressure load which are attributed to intake pressure oscillations. Despite measures to eliminate acoustic oscillations in the intake system, high-frequency pressure oscillations are shown to be caused by the backflow of air from the exhaust to the intake pipe when the valves open, exciting acoustic modes in the fluid volume.

The thorough understanding of the effects due to the fuel direct injection process in modern gasoline direct injection engines has become a mandatory task to meet the most demanding regulations in terms of pollutant emissions. Within this context, computational fluid dynamics proves to be a powerful tool to investigate how the in-cylinder spray evolution influences the mixture distribution, the soot formation and the wall impingement. In this work, the authors proposed a comprehensive methodology to simulate the air-fuel mixture formation into a gasoline direct injection engine under multiple operating conditions. At first, a suitable set of spray sub-models, implemented into an open-source code, was tested on the Engine Combustion Network Spray G injector operating into a static vessel chamber. Such configuration was chosen as it represents a typical gasoline multi-hole injector, extensively used in modern gasoline direct injection engines.

One seminal question that faces a vehicle's driver (either human or computer) is predicting the capability of the vehicle as it encounters upcoming terrain. A Location-Aware Adaptive Vehicle Dynamics (LAAVD) System is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. In contrast to current active safety systems, this system is predictive rather than reactive. This work provides the conceptual groundwork for the proposed system. The LAAVD System employs a predictor-corrector method in which the driver's input commands (throttle, brake, steering) and upcoming driving environment (terrain, traffic, weather) are predicted. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's throttle and brake control are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority.

A comparison between a hydraulic engine mount and a mixed mode magnetorheological (MR) fluid engine mount is presented. MR fluid is a smart material that changes viscosity in the presence of a magnetic field. In other words, without the presence of a magnetic field, the fluid is classified as a Newtonian fluid, however; with the presence of a magnetic field, the fluid becomes classified as a Bingham plastic. The working modes of the MR mount are squeeze and flow. Hydraulic mounts were developed to address the conflicting requirements of the engine vibration profile. The engine vibration profile can be classified as large displacement in the low frequency range and small displacement in the high frequency range. The hydraulic mount used in this study is an as received OEM mount. The elastomeric top and bottom of the hydraulic mount were used to create the MR mount. In the paper, the advantages and disadvantages of each mount are discussed in detail.

Magneto-rheological fluid squeeze mode investigations at CVeSS have shown that MR fluids show large force capabilities in squeeze mode. A novel MR squeeze mount was designed and built at CVeSS, and a dynamic mathematical model was developed, which considered the inertial effect and was validated by the test data. A variant engine mount that will be used for isolating vibration, based on the MR squeeze mode is proposed in the paper. The mathematical governing equations of the mount are derived to account for its operation with MR squeeze mode. The design method of a robust H✓ controller is addressed for the squeeze mount subject to parameter uncertainties in the damping and stiffness. The controller parameter can be derived from the solution of bilinear matrix inequalities (BMIs). The displacement transmissibility is constrained to be no more than 1.05 with this robust H✓ controller. The MR squeeze mount has a very large range of force used to isolate the vibration.

The Institute for Mechatronic Systems in Mechanical Engineering (IMS) designed a concept for a test rig, which enables the simulation of longitudinal, steering and vertical dynamics for a complete vehicle under laboratory conditions. The main part of the test rig concept is a shaft, which contains three constant velocity joints and two ball-spline supported length compensations. It connects the wheel hub of the test car to an electric motor. In addition a linear actuator is mounted to the middle part of the shaft and a hydraulic actuator replaces the suspension strut. These actuators can load the longitudinal, steering and vertical degree of freedom of the test car according to simulated driving maneuvers. A prototype of this concept is being built at the IMS lab. Beginning with a precise explanation of the test rig concept this paper discusses the control strategy for the rotational speed of the wheel hub of the car mounted on the test rig based on a simulation.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2009 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). Following GM's Vehicle Development Process (VDP), HEVT established team goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in extended-range hybrid electric vehicle. The competition requires participating teams to improve and redesign a stock Vue XE donated by GM. The result of this design process is an Extended-Range Electric Vehicle (E-REV) that uses grid electric energy and E85 fuel for propulsion. The vehicle design is predicted to achieve an SAE J1711 utility factor corrected fuel consumption of 2.9 L(ge)/100 km (82 mpgge) with an estimated all electric range of 69 km (43 miles) [1].

Referring to the transmission development, three different classifications of the power train are useful. These are the conventional power train with combustion-engined drive of the wheels, the electric power train with electromotive drive of the wheels and the hybrid power train with both types of drive. Due to this division, the micro hybrid belongs to the conventional power train while the serial hybrid is classified with the electric power train. Subdivisions of the electric power train are the decentralized drives near the axle shafts or the wheel hub drive and the central drive with differential. The choice of the electric motor is dependent on different influences such as the package, the costs or the application area. Furthermore the execution of the transmission system does influence the electric motor. Wheel hub drives are usually executed on wheel speed level or with single ratio transmission.

Faults in the intake and exhaust path of turbocharged common-rail Diesel engines can lead to an increase of emissions and performance losses. Standard fault detection strategies based on plausibility checks and trend checking of sensor data are not able to detect and isolate all faults appearing in the intake and exhaust path without employing additional sensors. By applying model based methods a limited sensor configuration can be used for fault detection. Therefore a model based fault diagnosis concept with parity equations is considered, [1]. In this contribution the fault diagnosis system, which comprises semi-physical thermodynamic turbocharger model, models of gas pressure in the intake and exhaust manifold, residual generation, residual to symptom transformation and fault diagnosis is presented.

Spray angle and penetration length data were taken under cold start conditions for a Direct Injection Spark Ignition engine to investigate the effect of transient conditions on spray development. The results show that during cold start, spray development depends primarily on fuel pressure, followed by Manifold Absolute Pressure (MAP). Injection frequency had little effect on spray development. The spray for this single hole, pressure-swirl fuel injector was characterized using high speed imaging. The fuel spray was characterized by three different regimes. Regime 1 comprised fuel pressures from 6 - 13 bar, MAPs from 0.7 - 1 bar, and was characterized by a large pre-spray along with large drop sizes. The spray angle and penetration lengths were comparatively small. Regime 2 comprised fuel pressures from 30 - 39 bar and MAPs from 0.51 - 0.54 bar. A large pre-spray and large drop sizes were still present but reduced compared to Regime 1.

A crucial step to designing and building more efficient vehicles is modeling powertrain energy consumption. While accurate modeling is indeed key to effective and efficient design, a fundamental understanding of the powertrain and auxiliary systems that contribute to the energy consumption of a vehicle is equally as important. This paper presents a methodology that has been packaged into a tool, called VTool (short for Vehicle Tool), which can be used to estimate the energy consumption of a vehicle powertrain. The method is intrinsically designed to foster understanding of the vehicle powertrain as it relates to energy consumption and losses while still providing reasonably accurate results. This paper briefly explains the methodology of VTool and demonstrates the capability of VTool as a design tool by presenting 4 example exercises.

The pre-prototype development of a simulated rule-based hybrid energy management strategy for a 2019 Chevrolet Blazer RS converted parallel P4 full hybrid is presented. A vehicle simulation model is developed using component bench data and validated using EPA-reported dynamometer fuel economy test data. A combined Willans line model is proposed for the engine and transmission, with hybrid control rules based on efficiency-derived engine power thresholds. Algorithms are proposed for battery state of charge (SOC) management including engine loading and one pedal strategies, with battery SOC maintained within 20% to 80% safe limits and charge balanced behavior achieved. The simulated rule-based hybrid control strategy for the hybrid vehicle has an energy consumption reduction of 20% for the Hot 505, 3.6% for the HwFET, and 12% for the US06 compared to the stock vehicle.

The influence of driver modeling and drive cycle target speed trace modification on vehicle dynamics within energy consumption simulations is studied. EPA dynamometer speed error criteria and the SAE J2951 Drive Quality Evaluation for Chassis Dynamometer Testing standard are applied to simulation outputs as proposed components of simulation validation, providing guidelines for acceptable vehicle speed outputs and allowing comparison of simulation results to reported EPA dynamometer test statistics. The combined effect of driver model tuning and drive cycle interpolation methods is investigated for the UDDS, HwFET and US06 drive cycles, with EPA-specified linearly interpolated speed trace and a PI controller driver as a baseline result.

The “Two-Drive-Transmission with Range-Extender” (called DE-REX) is an innovative hybrid powertrain concept using two electric motors and an internal combustion engine. The two electric motors are permanent magnet synchronous motors with a maximum power of 48 kW each. As combustion engine a 3 cylinder, turbocharged engine with a power of 65 kW is used. The aggregates are coupled to a transmission whose layout is characterized by consisting of two parallel 2-speed sub-transmissions. This layout offers a high flexibility and enables both parallel and series hybrid driving. The hybrid control unit (HCU) has to select the optimal driving mode and power distribution between the aggregates in regard to in some extend competing objectives like efficiency, emissions or driving comfort. In particular, the operation of the internal combustion engine with only two gear ratios is challenging.

The scope of this work is to propose a methodology to define multicomponent surrogate mixtures which describe the main evaporation characteristics of real gasoline fuels. Since real fuels are commonly complex mixtures with hundreds or thousands of hydrocarbons, their exact composition is generally not known. Only global characteristics are standardized. An accurate modeling of such complex mixtures in 3D-CFD requires the definition of a suitable surrogate. So far, surrogate mixtures have mostly been defined based on their combustion properties, such as ignition delay or burning velocity, irrespective of their evaporation characteristics. For this reason, in this work, a systematic study is carried out to develop a methodology to define mixtures of representative components that mimic the evaporation behavior of real fuels.

The application of Computational Fluid Dynamics (CFD) for three-dimensional (3D) combustion analysis coupled with detailed chemistry in engine development is hindered by its expensive computational cost. Chemistry computation may occupy as much as 90% of the total computational cost. In the present paper, a new two-step iso-octane combustion model was developed for spark-ignited (SI) engine to maximize computational efficiency while maintaining acceptable accuracy. Starting from the model constants of an existing global combustion model, the new model was developed using an approach based on sensitivity analysis to approximate the results of a reference skeletal mechanism. The present model involves only five species and two reactions and utilizes only one uniform set of model constants. The validation of the new model was performed using shock tube and real SI engine cases.

The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is excited about the opportunity to apply for participation in the next Advanced Vehicle Technology Competition. EcoCAR 3 is a new four year competition sponsored by the Department of Energy and General Motors with the intention of promoting sustainable energy in the automotive sector. The goal of the competition is to guide students from universities in North America to create new and innovative technologies to reduce the environmental impact of modern day transportation. EcoCAR 3, like its predecessors, will give students hands-on experience in designing and implementing advanced technologies in a setting similar to that of current production vehicles.