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Climate change due to greenhouse gas emissions has led to new vehicle emissions standards which in turn have led to a call for vehicle technologies to meet these standards. Modeling of vehicle fuel consumption and emissions emerged as an effective tool to help in developing and assessing such technologies, to help in predicting aggregate vehicle fuel consumption and emissions, and to complement traffic simulation models. The paper identifies the current state of the art on vehicle fuel consumption and emissions modeling and its utilization to test the environmental impact of the Intelligent Transportation Systems (ITS)’ measures and to evaluate transportation network improvements. The study presents the relevant models to ITS in the key classifications of models in this research area. It demonstrates that the trends of vehicle fuel consumption and emissions provided by current models generally do satisfactorily replicate field data trends.

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.

Ride control of military vehicles is challenging due to varied terrain and mission requirements such as operating weight. Achieving top speeds on rough terrain is typically considered a key performance parameter, which is always constrained by ride discomfort. Many military vehicles using passive suspensions suffer with compromised performance due to single tuning solution. To further stretch the performance domain to achieving higher speeds on rough roads, semi-active suspensions may offer a wide range of damping possibilities under varying conditions. In this paper, various semi-active control strategies are examined, and improvements have been made, particularly, to the acceleration-driven damper (ADD) strategy to make the approach more robust for varying operating conditions. A seven degrees of freedom ride model and a quarter-car model were developed that were excited by a random road process input modeled using an auto-regressive time series model.

During the last years mechatronic systems developed into one of the biggest drivers of innovation in the automotive industry. The start of production of systems like dual clutch transmission, lane departure warning systems and active suspensions proves this statement. These systems have an influence on the longitudinal, steering and vertical dynamics of the vehicle. That is why the interaction on vehicle level is crucial for an optimal result in the fields of efficiency, comfort, safety and dynamics. To optimize the interaction of mechatronic systems, in this paper a new test rig concept for a complete vehicle is presented. The so-called Car-in-the-Loop-concept is capable of realistically reproducing the loads, which act on the powertrain, the steering and the suspension during a test drive.

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.

A unique concept for a multi-body test rig enabling the simulation of longitudinal, steering and vertical dynamics was developed at the Institute for Mechatronic Systems (IMS) at TU Darmstadt. A prototype of this IMS test rig is currently being built. In conjunction with the IMS test rig, the Vehicle Terrain Performance Laboratory (VTPL) at Virginia Tech further developed a full car, seven degree of freedom (7 DOF) simulation model capable of accurately reproducing measured displacement, pitch, and roll of the vehicle body due to terrain excitation. The results of the 7 DOF car model were used as the reference input to the multi-body IMS test rig model. The goal of the IMS/VTPL joint effort was to determine whether or not a controller for the IMS test rig vertical actuator could accurately reproduce wheel displacements due to different measured terrain constraints.

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 Performance Margin (PM) is defined in this work as the ratio of the required tractive effort to the available tractive effort for the front and rear respectively. This simple definition stems from and incorporates many traditional handling metrics and is robust in its scope of applicability. The PM is implemented in an Intervention Strategy demonstrating its use to avoid situations in which the vehicle exceeds its handling capabilities. Results from a design case study are presented to show the potential efficacy of developing a PM-based control system.

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.

Modern thermal propulsion systems (TPS) as part of hybrid powertrains are becoming increasingly complex. They have an increased number of components in comparison to traditionally powered vehicles leading to increased demand in packaging requirements. Many of the components in these systems relate to achieving efficiency gains, weight saving and pollutant reduction. This includes turbochargers and diesel or gasoline particulate filters for example and these are known to be very sensitive to inlet boundary conditions. When overcoming packaging requirements, sub-optimal flow distributions throughout the TPS can easily occur. Moreover, the individual components are often designed in isolation assuming relatively flat and artificially quiescent inlet flow conditions in comparison to those they are actually presented with. Thus, some of the efficiency benefits are lost through reduced component aerodynamic efficiency.

This paper covers the development of a closed loop transaxle synchronization algorithm which was a key deliverable in the control system design for the L3 Enigma, a Battery Dominant Hybrid Electric Vehicle. Background information is provided to help the reader understand the history that lead to this unique solution of the input and output shaft synchronizing that typically takes place in a manual vehicle transmission or transaxle when shifting into a gear from another or into a gear from neutral when at speed. The algorithm stability is discussed as it applies to system stability and how stability impacts the speed at which a shift can take place. Results are simulated in The MathWorks Simulink programming environment and show how traction motor technology can be used to efficiently solve what is often a machine design issue. The vehicle test bed to which this research is applied is a parallel biodiesel hybrid electric vehicle called the Enigma.

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.

The chassis are subject to both road profile and engine or pump/motor vibration when a vehicle is moving on the road. The suspension is developed to reduce the effect of the road conditions to the chassis. The vibration from engine or pump/motor of hydraulic hybrid vehicles (HHV) will be also transmitted to the chassis and needs to be isolated. A mixed mode magnetorheological (MR) fluid mount is presented to isolate force vibration for a two degree of freedom (DOF) model based on quarter car concept. The MR fluid mount is designed to work in flow mode and squeeze mode separately and simultaneously. The skyhook control for the MR fluid mount is also been designed and simulated. Both displacement transmissibility and force transmissibility for each mode and for combined modes have been obtained. These simulation results present a basis for designing a more effective controller to control both the displacement transmissibility and force transmissibility.

Modern fatigue analysis techniques, that can provide reliable estimates of the service performance of components and structures, are finding increasing use in vehicle development programs. A major objective of such efforts is the prediction of the field performance of a fleet of vehicles as influenced by the host of design, manufacturing, and performance variables. An approach to this complex problem, based on the incorporation of probability theory in established life prediction methods, is presented. In this way, quantitative estimates of the lifetime distribution of a population are obtained based on anticipated, or specified, variations in component geometry, material processing sequences, and service loading. The application of this approach is demonstrated through a case study of an automotive transmission component.

The accuracy of computer-based ground vehicle durability and ride quality simulations depends on accurate representation of road surface topology as vehicle excitation data since most of the excitation exerted on a vehicle as it traverses terrain is provided by the terrain topology. It is currently not efficient to obtain accurate terrain profile data of sufficient length to simulate the vehicle being driven over long distances. Hence, durability and ride quality evaluations of a vehicle depend mostly on data collected from physical tests. Such tests are both time consuming and expensive, and can only be performed near the end of a vehicle's design cycle. This paper covers the development of a methodology to synthesize terrain profile data based on the statistical analysis of physically measured terrain profile data.

An online and real-time Condition Prediction system, so-called lifetime monitoring system, was developed at the Institute for Mechatronic Systems in Mechanical Engineering (IMS) of the TU Darmstadt, which is intended for implementation in standard control units of series production cars. Without additional hardware and only based on sensors and signals already available in a standard car, the lifetime monitoring system aims at recording the load/usage profiles of transmission components in aggregated form and at estimating continuously their remaining useful life. For this purpose, the dynamic transmission input and output torques are acquired realistically through sensor fusion. In a further step, the lifetime monitoring system is used as an input-module for the introduction of innovative procedures to more load appropriate dimensioning, cost-efficient lightweight design, failure-free operation and predictive maintenance of transmissions.

Binder jetting of sand molds and cores for metal casting provides a scalable and efficient means of producing metal components with complex geometric features made possible only by Additive Manufacturing. Topology optimization software that can mathematically determine the optimum placement of material for a given set of design requirements has been available for quite some time. However, the optimized designs are often not manufacturable using standard metal casting processes due to undercuts, backdraft and other issues. With the advent of binder-based 3D printing technology, sand molds and cores can be produced to make these optimized designs as metal castings.

Recently, the European Union has adopted a new regulation on Real-Driving-Emissions (RDE) and also China is considering RDE implementation into new China 6 legislation. The new RDE regulation is focused on measuring nitrogen oxides (NOx) and particulate number (PN) emissions of both light-duty gasoline and diesel vehicles under real world conditions. A supplemental RDE test procedure was developed for European type approval, which includes on-road testing with cars equipped with portable emission measurement systems (PEMS). This new regulation will significantly affect the engine calibrations and the exhaust gas aftertreatment. In this study the impact of the new RDE regulation on two recent EU 6b certified turbocharged direct injected gasoline vehicles has been investigated. A comparison of several chassis dyno drive cycles with two new defined on-road RDE cycles was performed.