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The adoption of the electronic controlled steering systems with new technologies has been extended in recent years. They have interactions with other complex vehicle subsystems and it is a hard task for the vehicle developer to find the best solution from huge number of the combination of parameter settings with track tests. In order to improve the efficiency of the steering system development, the authors had developed a steering bench test method for steering system using a Hardware-In-the-Loop Simulation (HILS). In the steering HILS system, vehicle dynamics simulation and the tie rod axial force calculation are required at the same time in the real-time simulation environment. The accuracy of the tie rod axial force calculation is one of the key factors to reproduce the vehicle driving condition. But the calculation cannot be realized by a commercial software for the vehicle dynamics simulation.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

A key element of General Motors' Advanced Propulsion Technology Strategy is the electrification of the automobile. The objectives of this strategy are reduced fuel consumption, reduced emissions and increased energy security/diversification. The introduction of hybrid vehicles was one of the first steps as a result of this strategy. To determine future opportunities and direction, an extensive study was completed to better understand the ability of Plug-in Hybrid Electric Vehicles (PHEV) and Extended-Range Electric Vehicles (E-REV) to address societal challenges. The study evaluated real world representative driving datasets to understand actual vehicle usage. Vehicle simulations were conducted to evaluate the merits of PHEV and E-REV configurations. As derivatives of conventional full hybrids, PHEVs have the potential to deliver a significant reduction in petroleum usage.

Accurate evaluation of vehicles' transient total power requirement helps achieving further improvements in vehicle fuel efficiency. When operated, the air-conditioning (A/C) system is the largest auxiliary load on a vehicle, therefore accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation models, such as "Autonomie," have been used by OEMs to evaluate vehicles' energy performance. However, the load from the A/C system on the engine or on the energy storage system has not always been modeled in sufficient detail. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic system simulation software MATLAB/Simulink® is frequently used by vehicle controls engineers to develop new and more efficient vehicle energy system controls.

A robotic driver has been designed on the basis of an analysis of a human driver's action in following a given driving schedule. The self-learning algorithm enables the robot to learn the vehicle characteristics without human intervention. Based on learned relationships, the robotic driver can determine an appropriate accelerator position and execute other operations through sophisticated calculations using the future scheduled vehicle speed and vehicle characteristics data. Compensation is also provided to minimize vehicle speed error. The robotic driver can reproduce the same types of exhaust emission and fuel economy data obtained with human drivers with good repeatability. It doesn't require long preparation time. Thereby making it possible to reduce experimentation work in the vehicle development process while providing good accuracy and reliability.

This paper describes a headway distance control system for platoon driving on an automated highway system (AHS). The system implemented on a test vehicle is described first, followed by a description of a vehicle control method based on the use of throttle and brake actuators. This method makes it possible to obtain the target acceleration and deceleration regardless of the vehicle speed range and the rate of acceleration or deceleration. Experimental and simulation results obtained with this method are presented. A control method is then described that uses inter-vehicle communication and laser radar to maintain a constant headway between vehicles. The results of simulations and driving tests conducted with three vehicles are presented to illustrate that the use of inter-vehicle communication is highly effective in improving headway control performance.

This paper assesses the potential improvement of automotive powertrain technologies 25 years into the future. The powertrain types assessed include naturally-aspirated gasoline engines, turbocharged gasoline engines, diesel engines, gasoline-electric hybrids, and various advanced transmissions. Advancements in aerodynamics, vehicle weight reduction and tire rolling friction are also taken into account. The objective of the comparison is the potential of anticipated improvements in these powertrain technologies for reducing petroleum consumption and greenhouse gas emissions at the same level of performance as current vehicles in the U.S.A. The fuel consumption and performance of future vehicles was estimated using a combination of scaling laws and detailed vehicle simulations. The results indicate that there is significant potential for reduction of fuel consumption for all the powertrains examined.

The durability test with road-load input is necessary for evaluating durability of body and chassis structure in automotive applications. This paper shows the method to analyze road-load input to a suspension system for development of a simple component level bench test. This method enables the extraction of the essential inputs to evaluate the durability of suspension parts using the transfer function (frequency response function) measured by Multi-axial Road Simulator and wheel force transducers. These extracted inputs contribute to development of a new realistic component bench test.

Increasing expectations for stability at high speed call for the improvement of cars' aerodynamic performance, in particular lift reduction. However, due to styling constraints, traditional spoilers must be avoided and replaced by other solutions like underfloor components. Flow simulation is expected to be a useful tool for lift prediction, but the conventional models used so far did not represent complex geometry details such as the engine compartment and underfloor, and accuracy was insufficient. In the present study, a full vehicle simulation model, including the engine compartment and underfloor details, was used. Other improvements were also made such as optimization of the computational grid and the setting of boundary conditions for reproducing wind tunnel experiments or actual driving, making it possible to predict lift variations due to vehicle geometry changes.

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.

This paper describes the method used to design the basic control algorithm of a lane-keeping support system that is intended to assist the driver's steering action. Lane-keeping control has been designed with steering torque as the control input without providing a minor loop for the steering angle. This approach was taken in order to achieve an optimum balance of lane-keeping control, ease of steering intervention by the driver and robustness. The servo control system was designed on the basis of H2 control theory. Robustness against disturbances, vehicle nonlinearity and parameter variation was confirmed by μ - analysis. The results of computer simulations and driving tests have confirmed that the control system designed with this method provides the intended performance.

On-board voice-interaction systems such as a voice-activated system or a text -to-speech (TTS) system enable drivers to operate devices or to obtain desired information without relying on visual processes. These systems are aimed to reduce the driver's workload, but there is a concern about their possible effect on mental distraction. This paper describes driving simulator tests that were conducted to examine the potential influence of such systems on driver's mental distraction. The results obtained for all of the indices show that the mental distraction level when operating a voice-activated system is significantly lower than that of a traditional manually operated system.

Lock-up operation of an automatic transmission is known as one good method of improving fuel economy. However, locking up the transmission at low vehicle speeds can often cause undesirable vibration or booming noise. Slip control of the lock-up clutch can resolve these problems, but the speed difference of the lock-up clutch needs to be controlled at a certain value. This control system has to overcome large changes in the parameters of the lock-up system at low vehicle speeds and also changes with regard to the speed ratio in a continuously variable transmission (CVT). In this study, this complex non-linear system has been modeled as a first-order linear parameter varying (LPV) system. A robust control algorithm was applied taking various disturbances into account to design a new slip lock-up control system.

This paper discusses the development of combination vehicle stability program (CVSP) at Visteon. It will describe why stability control is needed for combination vehicles and how the vehicle stability can be improved. We propose and evaluate controller structures and design methods for CVSP. These include driver's intent identification, combination vehicle status estimation and control, and fault detection / tolerance. In this paper, the braking and steering dynamics of car-trailer and tractor-semitrailer combinations, and the brake systems which should be used extensively to increase the stability of combination vehicles are presented. Also our development platform is introduced and the combination vehicle simulation results are presented. The definition of combination vehicles in this paper includes car-trailer and commercial tractor-semitrailer combinations since their vehicle dynamics are based on the same equations of motion.

A set of functions for characterizing the mechanical properties of a steering “short gear” is described. They cover the kinematic, stiffness, assist, and friction performance of a power assisted (or manual) steering gear from the input shaft to the inner ends of the tie rods. Their use in describing the performance of a generalized steering gear is described. They have particular application to describing the steering feel performance of a vehicle. They can be used to specify the steering subsystem performance for desired steering feel for a given vehicle. They can also be used for experimental characterization of steering subsystems, can be used in vehicle dynamics simulations, and can be synthesized from a set of vehicle level performance targets. Along with their description, their use in simulation and methods to synthesize their values are described.

NASA has long recognized the advantages of providing improved information interfaces to EVA astronauts and has pursued this goal through a number of development programs over the past decade. None of these activities or parallel efforts in industry and academia has so far resulted in the development of an operational system to replace or augment the current extravehicular mobility unit (EMU) Display and Controls Module (DCM) display and cuff checklist. Recent advances in display, communications, and information processing technologies offer exciting new opportunities for EVA information interfaces that can better serve the needs of a variety of NASA missions. Hamilton Sundstrand Space Systems International (HSSSI) has been collaborating with Simon Fraser University and others on the NASA Haughton Mars Project and with researchers at the Massachusetts Institute of Technology (MIT), Boeing, and Symbol Technologies in investigating these possibilities.

Computer simulation of extravehicular activity (EVA) is increasingly being used in planning and training for EVA. A space suit model is an important, but often overlooked, component of an EVA simulation. Because of the inherent difficulties in collecting angle and torque data for space suit joints in realistic conditions, little data exists on the torques that a space suit’s wearer must provide in order to move in the space suit. A joint angle and torque database was compiled on the Extravehicular Maneuvering Unit (EMU), with a novel measurement technique that used both human test subjects and an instrumented robot. Using data collected in the experiment, a hysteresis modeling technique was used to predict EMU joint torques from joint angular positions. The hysteresis model was then applied to EVA operations by mapping out the reach and work envelopes for the EMU.

Evaluations of dummy injury readings obtained in regulatory crash tests and new car assessment program tests provide indices for the development of crash safety performance in the process of developing new vehicles. Based on these indices, vehicle body structures and occupant restraint systems are designed to meet the required occupant injury criteria. There are many types of regulatory tests and new car assessment program tests that are conducted to evaluate vehicle safety performance in side impacts. Factoring all of the multiple test configurations into the development of new vehicles requires advanced design capabilities based on a good understanding of the mechanisms producing dummy injury readings. In recent years, advances in computer-aided engineering (CAE) tools and computer processing power have made it possible to run simulations of occupant restraint systems such as side airbags and seatbelts.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

The progress of computer technology and CAE methodology makes it possible to simulate dummy injury readings in vehicle crash simulations. Dummy neck injuries are generally more difficult to simulate than injuries to other regions such as the head or chest. Accordingly, improving the accuracy of dummy neck injury data is a major concern in frontal occupant safety simulations. This paper describes the use of an advanced airbag modeling methodology to improve the accuracy of dummy neck injury readings. First, the following items incorporated in the advanced airbag model are explained. (1) The Finite Point Method (FPM) is used to simulate the flow of gas. (2) A folding model is applied to simulate the folded condition. (3) The fabric material properties used in the simulation take into account anisotropy in the fiber directions and the nonlinear, hysteresis characteristics of stiffness.