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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.

Driving cycles play a fundamental role in the design of components, in the optimization of control strategies for drivetrain topologies, and in the identification of vehicle properties. The focus on a single or a few test cycles results in a risk of non-optimal or even poor design regarding the real usage profiles. Ideally, multiple different driving cycles that are representative of the real and scattering operating conditions are used. Therefore, tools for the stochastic generation of representative driving cycles are required, and many works have addressed this issue with different approaches. Until now, the stochastic generation of representative testing cycles has been limited to low dimensionality, and only a few works have studied higher dimensionality using Markov chain theory. However, it is mandatory to create tools that can stochastically generate multidimensional cycles incorporating all relevant operating conditions and maintaining signal dependency at the same time.

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.

Currently, the final stages of chassis development are conducted on prototype vehicles, requiring vehicle manufacturers to dedicate copious resources to the development of each new vehicle platform. The objective of this work is to provide development engineers a system identification tool enabling them to use modeling and simulation to better estimate the required vehicle system parameters. This work develops a parameter identification method for existing vehicle models in which measured terrain data is used as the model excitation. The model was validated using a variety of excitation events and shown to provide accurate estimations of a vehicle’s roll, pitch, and vertical displacement.

In this paper a yaw stability control algorithm along with an emergency roll control strategy have been developed. The yaw stability controller and emergency roll controller were both developed using linear two degree-of-freedom vehicle models. The yaw stability controller is based on Lyapunov stability criteria and uses vehicle lateral acceleration and yaw rate measurements to calculate the corrective yaw moment required to stabilize the vehicle yaw motion. The corrective yaw moment is then applied by means of a differential braking strategy in which one wheel is selected to be braked with appropriate brake torque applied. The emergency roll control strategy is based on a rollover coefficient related to vehicle static stability factor. The emergency roll control strategy utilizes vehicle lateral acceleration measurements to calculate the roll coefficient. If the roll coefficient exceeds some predetermined threshold value the emergency roll control strategy will deploy.

The U.S. Army Tank Automotive Research Development and Engineering Center (TARDEC) and the U.S. Army Corps of Engineers (USACE) are improving modeling and simulation technologies in order to predict the performance of Army ground platforms with a high degree of confidence. In order to provide a framework within which to evaluate the simulation technologies and provide a measure of the progress of the effort, a suite of virtual test operating procedures are being implemented. This framework is called the Virtual Evaluation Suite (VES). It is applicable to the study of ground vehicle stability, handling, ride, mobility, and durability over all terrains under all weather conditions. Although developed in order to evaluate simulation technologies, the VES may be considered a simulation that could be used to exercise any ground platform model that meets the VES standard vehicle interface.

A high fidelity seat suspension model, which can be used for ride quality predictions, is developed in this work. The coil-spring seat suspension model includes unique nonlinear forms for the stiffness and damping characteristics. This is the first paper to consider the nonlinear geometric effects of the suspension, derive the coil-spring suspension model from physical principles, and compare theoretical and experimental results. A simplified nonlinear form is achieved via an admissible function describing the vertical suspension deflection as a function of the lateral position. This simplified nonlinear form is compared to experimental data and demonstrated to have exceptional fidelity.

A Vehicle Dynamics and Mobility Server (VDMS) is being developed by the U.S. Army to perform real-time high-fidelity simulation of robotic vehicle concepts. It allows a set of conceptual Unmanned Ground Vehicles (UGVs) to be selected and configured for the purposes of evaluating their mobility performance in a simulated battlefield scenario. VDMS includes real-time ground vehicle models operating over high-resolution digital terrain. The models consist of three-dimensional multi-body vehicle dynamics, off-road vehicle-soil interaction, collision detection and obstacle negotiation code, and autonomous control algorithms. A minimally completed VDMS was used in an RDEC Federation Calibration Experiment (CalEx) in October 2001 to predict the mobility of ten robotic scout vehicles. This paper presents the rationale, requirements, design, and implementation of VDMS. It also briefly discusses other possible applications of VDMS and the future direction of VDMS.

Load data representing severe customer usage is required during the chassis development process. The use of road profiles and vehicle models to predict chassis loads is currently being researched; this research hinges on the ability to accurately measure road profiles. This work focuses on detecting possible signal defects such as leaves on the ground, reflecting surfaces, or narrow roadway gaps. The objective of this work is to develop a simulation procedure that checks the measured road profile for plausibility. The position of the vehicle body is recorded as part of the typical road profiling process. Ideally, a mathematical model can predict the body position from a road profile. The first step in verifying the plausibility of road profiles is to predict the body position. Next, the measured body position is compared to the predicted body position for the road profile in question. New criteria for plausibility checking are a major contribution of this work.

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.

In order to offer a wide range of driving experiences to their customers, original equipment manufacturers implement different driving programs. The driver is capable of manually switching between these programs which alter drivability parameters in the engine control unit. As a result, acceleration forces and gradients are modified, changing the perceived driving experience. Nowadays, drivability is calibrated iteratively through road testing. Hence, the resulting set of parameters incorporated within the engine control unit is strongly dependent on the individual sentiments and decisions of the test engineers. It is shown, that implementing a set of objective criteria offers a way to reduce the influences of personal preferences and sentiments in the drivability calibration process. In combination with the expertise of the test engineers, the desired vehicle behavior can be formalized into a transient set point sequence to give final shape to the acceleration behavior.

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.

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.

Accurate terrain models provide the chassis designer with a powerful tool to make informed design decisions early in the design process. It is beneficial to characterize the terrain as a stochastic process, allowing limitless amounts of synthetic terrain to be created from a small number of parameters. A continuous-state Markov chain is proposed as an alternative to the traditional discrete-state chain currently used in terrain modeling practice. For discrete-state chains, the profile transitions are quantized then characterized by a transition matrix (with many values). In contrast, the transition function of a continuous-state chain represents the probability density of transitioning between any two states in the continuum of terrain heights. The transition function developed in this work uses a location-scale distribution with polynomials modeling the parameters as functions of the current state.

A virtual, all-season test site for use in real-time vehicle simulators and mobility models was constructed of an Army firing range in Northern Vermont. The virtual terrain will mimic the terrain of our Virtual Data Acquisition and Test Site (VDATS) at Ethan Allen Firing Range (EAFR). The objective is to realistically simulate on- and off-road vehicle performance in all weather conditions for training and vehicle design for the US Army. To this end, several spatial datasets were needed to accurately map the terrain and estimate the state-of-the-ground and terrain strength at different times of the year. The terrain strength is characterized by terramechanics properties used in algorithms to calculate the forces at the vehicle-terrain interface. The performance of the real vehicles will be compared to the simulated vehicle performance of operator-in-the-loop and unmanned vehicles for validation of the simulations.

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.

In the context of off-road vehicle simulations, deformable terrain models mostly fall into three categories: simple visualization of the deformed terrain only, use of empirical relationships for the deformation, or finite/discrete element approaches for the terrain. A real-time vehicle dynamics simulation with a physics-based tire model (brush, ring or beam-based models) requires a terrain model that accurately reflects the deformation and response of the soil to all possible inputs of the tire in order to correctly simulate the response of the vehicle. The real-time requirement makes complex finite/discrete element approaches unfeasible, and the use of a ring or beam -based tire model excludes purely empirical terrain models. We present the development of a three-dimensional vehicle/terrain interaction model which is comprised of a tire and deformable terrain model to be used with a real-time vehicle dynamics simulator.

Hybrid powertrains derive fuel consumption benefits from using an electric motor. These benefits are more significant in city traffic than on the highway and depend on the vehicle and the driving style. Further detailed research on the fuel consumption of hybrid powertrains during drive-off procedures is rarely found in the literature. Therefore, this study focuses on analyzing the potential of a mild-hybrid powertrain, in which the electric motor is integrated with the transmission (P2.5 concept). The fuel consumption and thermal load in the drive-off element, a wet frictional clutch, are analyzed for a city cycle with a focus on the first drive-off procedure for different driving styles. Particular attention is paid to the influence of different driving styles on the torque demands of the electric motor. These simulations are realized with a so-called backward-forward model. The backward-facing part enables following a given driving cycle without considering a driver model.