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This paper describes the design and implementation of the SEA, Ltd. Brake and Throttle Robot (BTR). Presented are the criteria used in the initial design and the development and testing of the BTR, as well as some test results achieved with the device. The BTR is designed for use in automobiles and light trucks. It is based on a servomotor driven ballscrew, which in turn operates either the brake or accelerator. It is easily portable from one vehicle to another and compact enough to fit even smaller vehicles. The BTR is light enough so as to have minimal effect on the measurement of vehicle parameters. The BTR is designed for use as a stand-alone unit or as part of a larger control system such as the Automated Test Driver (ATD) yet allows for the use of a test driver for safety, as well as test selection, initiation, and monitoring. Installation in a vehicle will be described, as well as electronic components that support the BTR.

The assessment of fuel economy of new vehicles is typically based on regulatory driving cycles, measured in an emissions lab. Although the regulations built around these standardized cycles have strongly contributed to improved fuel efficiency, they are unable to cover the envelope of operating and environmental conditions the vehicle will be subject to when driving in the “real-world”. This discrepancy becomes even more dramatic with the introduction of Connectivity and Automation, which allows for information on future route and traffic conditions to be available to the vehicle and powertrain control system. Furthermore, the huge variability of external conditions, such as vehicle load or driver behavior, can significantly affect the fuel economy on a given route. Such variability poses significant challenges when attempting to compare the performance and fuel economy of different powertrain technologies, vehicle dynamics and powertrain control methods.

Vehicle dynamics models employed in heavy truck simulation often treat the semitrailer as a torsionally rigid member, assuming zero deflection along its longitudinal axis as a moment is applied to its frame. Experimental testing, however, reveals that semitrailers do twist, sometimes enough to precipitate rollover when a rigid trailer may have remained upright. Improving the model by incorporating realistic trailer roll stiffness values can improve assessment of heavy truck dynamics, as well as an increased understanding of the effectiveness of stability control systems in limit handling maneuvers. Torsional stiffness measurements were conducted by the National Highway Traffic Safety Administration (NHTSA) for eight semitrailers of different types, including different length box vans, traditional and spread axle flat beds, and a tanker.

Automating road vehicle control can increase the range and reliability of dynamic testing. Some tests, for instance, specify precise steering inputs which human test drivers are only able to approximate, adding uncertainty to the test results. An automated steering system has been developed which is capable of removing these limitations. This system enables any production car or light truck to follow a user-defined path, using global position feedback, or to perform specific steering sequences with excellent repeatability. The system adapts itself to a given vehicle s handling characteristics, and it can be installed and uninstalled quickly without damage or permanent modification to the vehicle.

The Ohio State University Center for Intelligent Transportation Research (CITR) has developed three automated vehicles demonstrating advanced cruise control, automated steering control for lane keeping, and autonomous behavior including automated stopping and lane changes in reaction to other vehicles. Various sensors were used, including a radar reflective stripe system and a vision based system for lane position sensing, a radar system and a scanning laser rangefinding system for the detection of objects ahead of the vehicle, and various supporting sensors including side looking radars and an angular rate gyroscope. These vehicles were demonstrated at the National Automated Highway System Consortium (NAHSC) 1997 Technical Feasibility Demonstration in a scenario involving mixed autonomous and manually driven vehicles. This paper describes the demonstration, the vehicle sensing, control, and computational hardware, and the vehicle control software.

This paper describes the development of a more accurate shock absorber model in order to obtain better vehicle simulation results. Previous shock models used a single spline to represent shock force versus shock velocity curves. These models produced errors in vehicle simulations because the damper characteristics are better represented by the application of a hysteresis loop in the model. Thus, a new damper model that includes a hysteresis loop is developed using Matlab Simulink. The damper characteristics for the new model were extracted from measurements made on a shock dynamometer. The new model better represents experimental shock data. The new shock model is incorporated into two different lumped-parameter vehicle models: one is a three degree-of-freedom vehicle handling model and the other is a seven degree-of-freedom vehicle ride model. The new damper model is compared with the previous model for different shock mileages (different degrees of wear).

The paper discusses the development of a model for the 2006 BMW 330i for the National Advanced Driving Simulator's (NADS) vehicle dynamics simulation, NADSdyna. The front and rear suspensions are independent strut and link type suspensions modeled using recursive rigid-body dynamics formulations. The suspension springs and shock absorbers are modeled as force elements. The paper includes parameters for front and rear semi-empirical tire models used with NADSdyna. Longitudinal and lateral tire force plots are also included. The NADSdyna model provides state-of-the-art high-fidelity handling dynamics for real-time hardware-in-the-loop simulation. The realism of a particular model depends heavily on how the parameters are obtained from the actual physical system. Complex models do not guarantee high fidelity if the parameters used were not properly measured. Methodologies for determining the parameters are detailed in this paper.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

Modern passenger cars are being equipped with advanced driver assistance systems such as lane departure warning, collision avoidance systems, adaptive cruise control, etc. Testing for operation and effectiveness of these warning systems involves interaction between vehicles. While dealing with multiple moving vehicles, obtaining discriminatory results is difficult due to the difficulty in minimizing variations in vehicle separation and other parameters. This paper describes test strategies involving an automated test driver interacting with another moving vehicle. The autonomous vehicle controls its state (including position and speed) with respect to the target vehicle. Choreographed maneuvers such as chasing and overtaking can be performed with high accuracy and repeatability that even professional drivers have difficulty achieving. The system is also demonstrated to be usable in crash testing.

During a motor-vehicle collision, an occupant may interact with a variety of interior structures. The material properties and construction of these structures can directly affect the occupant's kinetic response. Simulation tools such as MADYMO (Mathematical Dynamical Models) can be used to estimate the forces imparted to an occupant for injury mechanism and causation evaluation relative to a particular event. Depending on the impact event and the specific injury mechanism being evaluated, the selection of proper material characteristics can be quite important. A comprehensive literature review of MADYMO studies illustrates the prevalent use of generic material characteristics and the need for improved property estimation and implementation methods.

This paper presents the details of the model for the physical steering system used on the National Advanced Driving Simulator. The system is basically a hardware-in-the-loop (steering feedback motor and controls) steering system coupled with the core vehicle dynamics of the simulator. The system's torque control uses cascaded position and velocity feedback and is controlled to provide steering feedback with variable stiffness and dynamic properties. The reference model, which calculates the desired value of the torque, is made of power steering torque, damping function torque, torque from tires, locking limit torque, and driver input torque. The model also provides a unique steering dead-band function that is important for on-center feel. A Simulink model of the hardware/software is presented and analysis of the simulator steering system is provided.

Aircraft incidents and accidents in icing are often the result of degradation in performance and control. However, current ice sensors measure the amount of ice and not the effect on performance and control. No processed aircraft performance degradation information is available to the pilot. In this paper research is reported on a system to estimate aircraft performance and control changes due to ice, then use this information to automatically operate ice protection systems, provide aircraft envelope protection and, if icing is severe, adapt the flight controls. Key to such a safety system would be he proper communication to, and coordination with, the flight crew. This paper reviews the basic system concept, as well as the research conducted in three critical areas; aerodynamics and flight mechanics, aircraft control and identification, and human factors.

It is commonly recommended to use infant/child restraints in the rear seat, and that until an infant reaches certain age, weight and height criteria, the infant restraint should be placed rear facing. This paper will describe the injuries suffered by an infant that was restrained in a forward-facing child seat placed in the front passenger seating position during a real world collision. Based on this collision, a full-scale vehicle to barrier impact test was performed. For this test, two 6-month-old CRABI dummies were used in identical child restraints. One of the restraints was placed in the front passenger seat in a forward facing configuration, and the other was placed in the right rear seating position in a rear-facing configuration. This paper provides a detailed discussion of the results of this test, including comparisons of the specific kinematics for both the restraint/child dummy configurations.

A determination of the vehicle states and tire forces is critical to the stability of vehicle dynamic behavior and to designing automotive control systems. Researchers have studied estimation methods for the vehicle state vectors and tire forces. However, the accuracy of the estimation methods is closely related to the employed model. In this paper, tire lag dynamics is introduced in the model. Also application of estimation methods in order to improve the model accuracy is presented. The model is developed by using the global searching algorithm, a Genetic Algorithm, so that the model can be used in the nonlinear range. The extended Kalman filter and sliding mode observer theory are applied to estimate the vehicle state vectors and tire forces. The obtained results are compared with measurements and the outputs from the ADAMS full vehicle model. [15]

This year, in the third year of FutureTruck competition, the Ohio State University team has taken the challenge to convert a 2002 Ford Explorer into a more fuel efficient and environmentally friendly SUV. This goal was achieved by use of a post-transmission, charge sustaining, parallel hybrid diesel-electric drivetrain. The main power source is a 2.5-liter, 103 kW advanced CIDI engine manufactured by VM Motori. A 55 kW Ecostar AC induction electric motor provides the supplemental power. The powertrain is managed by a state of the art supervisory control system which optimizes powertrain characteristics using advanced energy management and emission control algorithms. A unique driver interface implementing advanced telematics, and an interior designed specifically to reduce weight and be more environmentally friendly add to the utility of the vehicle as well as the consumer appeal.

The single-parameter, in-process monitor and automatic control systems for the resistance spot welding process have been studied by many investigators. Some of these have already been commercialized and used by sheet metal fabricators. These control systems operate primarily on one of the three process parameters: maximum voltage or voltage drop, dynamic resistance, or thermal expansion between electrodes during nugget formation. Control systems based on voltage or dynamic resistance have been successfully implemented for industrial applications. A great amount of experience on these two control methods has been accumulated through trial-and-error approaches. The expansion-based control system is not commonly utilized due to lack of experience and understanding of the process. Since the expansion displacement between electrodes during welding responds directly to the weld nugget formation, this control parameter provides a better means to produce more precise spot welds.

The rapid development of driver assistance systems, such as lane-departure warning (LDW) and lane-keeping support (LKS), along with widely publicized reports of automated vehicle testing, have created the expectation for an increasing amount of vehicle automation in the near future. As these systems are being phased in, the coexistence of automated vehicles and human-driven vehicles on roadways will be inevitable and necessary. In order to develop automated vehicles that integrate well with those that are operated in traditional ways, an appropriate understanding of human driver behavior in normal traffic situations would be beneficial. Unlike many research studies that have focused on collision-avoidance maneuvering, this paper analyzes the behavior of human drivers in response to cut-in vehicles moving at similar speeds. Both automated and human-driven vehicles are likely to encounter this scenario in daily highway driving.

The Ohio State University EcoCAR 3 team is building a plug-in hybrid electric vehicle (PHEV) post-transmission parallel 2016 Chevrolet Camaro. With the end-goal of improving fuel economy and reducing tail pipe emissions, the Ohio State Camaro has been fitted with a 32 kW alternator-starter belt coupled to a 119 kW 2.0L GDI I4 engine that runs on 85% ethanol (E85). The belted alternator starter (BAS) which aids engine start-stop operation, series mode and torque assist, is powered by an 18.9 kWh Lithium Iron Phosphate energy storage system, and controlled by a DC-AC inverter/controller. This report details the modeling, calibration, testing and validation work done by the Ohio State team to fast track development of the BAS system in Year 2 of the competition.

A Software-in-the-Loop (SIL) simulation is presented here wherein control algorithms for the Anti-lock Braking System (ABS) and Roll Stability Control (RSC) system were developed in Simulink. Vehicle dynamics models of a 6×4 cab-over tractor and two trailer combinations were developed in TruckSim and were used for control system design. Model validation was performed by doing various dynamic maneuvers like J-Turn, double lane change, decreasing radius curve, high dynamic steer input and constant radius test with increasing speed and comparing the vehicle responses obtained from TruckSim against field test data. A commercial ESC ECU contains two modules: Roll Stability Control (RSC) and Yaw Stability Control (YSC). In this research, only the RSC has been modeled. The ABS system was developed based on the results obtained from a HIL setup that was developed as a part of this research.

Fault diagnosis for automotive systems is driven by government regulations, vehicle repairability, and customer satisfaction. Several methods have been developed to detect and isolate faults in automotive systems, subsystems and components with special emphasis on those faults that affect the exhaust gas emission levels. Limit checks, model-based, and knowledge-based methods are applied for diagnosing malfunctions in emission control systems. Incipient and partial faults may be hard to detect when using a detection scheme that implements any of the previously mentioned methods individually; the integration of model-based and knowledge-based diagnostic methods may provide a more robust approach. In the present paper, use is made of fuzzy residual evaluation and of a fuzzy expert system to improve the performance of a fault detection method based on a mathematical model of the engine.