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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.

As vehicle development timelines continue to shorten, it is necessary for the full vehicle NVH engineer to be able to predict performance without actual prototypes. There has been significant advancement in the accuracy of finite element modeling techniques of trimmed bodies; however accuracy is still low in the road noise mid frequency range from 150-400Hz. Also, calculation times for these frequencies are long, with very large results files in some cases. To alleviate these limitations, a Hybrid approach has been used, where a finite element suspension and drive train model is coupled with a test based Frequency Response Function (FRF) model of the trimmed body. The predicted road noise level was compared to actual vehicle tests and exhibited excellent correlation.

Over the last decade, many methods have been proposed for estimating the in-cylinder combustion pressure or the torque from instantaneous crankshaft speed measurements. However, such approaches are typically computationally expensive. In this paper, an entirely different approach is presented to allow the real-time estimation of the in-cylinder pressures based on crankshaft speed measurements. The technical implementation of the method will be presented, as well as extensive results obtained for a V-6 S.I. engine while varying spark timing, engine speed, engine load and EGR. The method allows to estimate the in-cylinder pressure with an average estimation error of the order of 1 to 2% of the peak pressure. It is very general in its formulation, is statistically robust in the presence of noise, and computationally inexpensive.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

This study investigated the jackknife stability of Class VIII double tractor-trailer combination vehicles that had mixed braking configurations between the tractor and trailers and dolly (e.g. ECBS disc brakes on the tractor and pneumatic drum brakes on the trailers and dolly). Brake-in-turn maneuvers were performed with varying vehicle loads and surface conditions. Conditions with ABS ON for the entire vehicle (and select-high control algorithm on the trailers and dolly) found that instabilities (i.e. lane excursions and/or jackknifes) were exhibited under conditions when the surface friction coefficient was 0.3. It was demonstrated that these instabilities could be avoided while utilizing a select-low control algorithm on the trailers and dolly. Simulation results with the ABS OFF for the tractor showed that a tractor equipped with disc brakes had greater jackknife stability.

During Phase VI of the National Highway Traffic Safety Administration's (NHTSA) Light Vehicle Rollover Research Program, three of the twenty-six light vehicles tested exhibited significant response asymmetries with respect to left versus right steer maneuvers. This paper investigates possible vehicle asymmetric characteristics and unintended inputs that may cause vehicle asymmetric response. An analysis of the field test data, results from suspension and steering parameter measurements, and a summary of a computer simulation study are also given.

This paper presents the development of a CarSim model of an All-Terrain Vehicle (ATV) that can be used to predict the handling and stability characteristic of the vehicle. The inertia and suspension characteristics of a subject ATV are measured and a model of the ATV is built in CarSim based on the measurements. A simplified suspension model is developed to convert the suspension compliance measurements into parameters suitable to a CarSim model. Procedures used to apply vehicle mass, inertia and suspension kinematics data in CarSim are also shown. The model is evaluated using predictions of vehicle response during a constant radius circle test. The simulation results of the maneuver are compared with the field test results shown in a recent CPSC report on ATV’s. Similar cornering characteristics are found in both results. Modifications are made to the model to study how changes to the ATV affect performance.

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 component response synthesis approach utilizing frequency response function (FRF) has been used to analyze the dynamic interaction of two or more vehicle components coupled at discrete interface points. This method is somewhat suitable for computing higher frequency response because experimental component FRFs can be incorporated into the formulation directly. However its calculations are quite sensitive to measurement errors in the FRFs due to the several matrix inversion steps involved. In the past, researchers have essentially used a combined direct inverse and truncated singular valued decomposition (TSVD) technique to ensure a stable calculation, which is typically applied semi-empirically due to the lack of understanding of the influence of measurement error.

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.

Recent studies in sheet metal forming, conducted at universities world wide, emphasize the development of computer aided techniques for process simulation. To be practical and acceptable in a production environment, these codes must be easy to use and allow relatively quick solutions. Often, it is not necessary to make exact predictions but rather to establish the influence of process variables upon part quality, tool stresses, material flow, and material thickness variation. In cooperation with its industrial partners, the ERC for Net Shape Manufacturing of the Ohio State University has applied a number of computer codes for analysis and design of sheet metal forming operations. This paper gives a few selected examples taken from automotive applications and illustrates practical uses of computer simulations to improve productivity and reduce tool development and manufacturing costs.

Autonomous vehicles are expected to change our lives with significant applications like on-demand, shared autonomous taxi operations. Considering that most vehicles in a fleet are parked and hence idle resources when they are not used, shared on-demand services can utilize them much more efficiently. While ride hailing of autonomous vehicles is still very costly due to the initial investment, a shared autonomous vehicle fleet can lower its long-term cost such that it becomes economically feasible. This requires the Shared Autonomous Vehicles (SAV) in the fleet to be in operation as much as possible. Motivated by these applications, this paper presents a simulation environment to model and simulate shared autonomous vehicles in a geo-fenced urban setting.

This paper describes the procedures used to reduce the tonal noise of a class eight truck engine timing gear train that was initially found to be objectionable under idle operating conditions. Initial measurements showed that the objectionable sounds were related to the fundamental gear mesh frequency, and its second and third harmonics. Experimental and computational procedures used to study and trouble-shoot the problem include vibration and sound measurements, transmission error analysis of the gears under light load condition, and a dynamic analysis of the drive system. Detail applications of these techniques are described in this paper.

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.

As we continue to create ever-lighter road vehicles, the challenge of balancing weight reduction and structural performance also continues. One of the key parts this occurs on is the hood, where lighter materials (e.g. aluminum) have been used. However, the aerodynamic loads, such as hood lift, are essentially unchanged and are driven by the front fascia and front grille size and styling shape. This paper outlines a combination CFD/FEA prediction method for hood deflection performance at high speeds, by using the surface pressures as boundary conditions for a FEA linear static deflection analysis. Additionally, custom post-processing methods were developed to enhance flow analysis and understanding. This enabled the modification of existing test methods to further improve accuracy to real world conditions. The application of these analytical methods and their correlation with experimental results are discussed in this paper.

This paper discusses the derivation and validation of planar models of articulated vehicles that were developed to analyze jackknife stability on low-μ surfaces. The equations of motion are rigorously derived using Lagrange's method, then linearized for use in state-space models. The models are verified using TruckSim™, a popular nonlinear solid body vehicle dynamics modeling package. The TruckSim™ models were previously verified using extensive on-vehicle experimental data [1, 2]. A three-axle articulated model is expanded to contain five axles to avoid lumping the parameters for the drive and semitrailer tandems. Compromises inherent in using the linearized models are discussed and evaluated. Finally, a nonlinear tire cornering force model is coupled with the 5-axle model, and its ability to simulate a jackknife event is demonstrated. The model is shown to be valid over a wide range of inputs, up to and including loss of control, on low-and-medium-μ surfaces.

Despite a large body of analytical work characterizing the dynamic motion of planetary gears, supporting experimental data is limited. Experimental results are needed to support computer modeling and offer practical optimization guidelines to gear designers. This paper presents the design and implementation of a test facility and precision test fixtures for accurate measurement of planetary gear vibration at operating conditions. Acceleration measurements are made on all planetary bodies under controlled torque/speed conditions. Custom, high-precision test fixtures accommodate instrumentation, ensure accurate alignment, help isolate gear dynamics, and allow for variability in future testing. Results are compared with finite element and lumped parameter models.

This paper describes the development and implementation of an accurate and repeatable path-following algorithm focused ultimately on vehicle testing. A compact, lightweight, and portable hardware package allows easy installation and negligible impact on the vehicle mass, even for the smallest automobile. Innovative features include the ability to generate a smooth, evenly-spaced path vector regardless the quality of the given path. The algorithm proposed in this work is suitable for testing in a controlled environment. The system was evaluated in simulation and performed well in road tests at low speeds.

An important part of automotive driving assistance systems and autonomous vehicles is speed optimization and traffic flow adaptation. Vehicle sensors and wireless communication with surrounding vehicles and road infrastructure allow for predictive control strategies taking near-future road and traffic information into consideration to improve fuel economy. For the development of autonomous vehicle speed control algorithms, it is imperative that the controller can be evaluated under different realistic driving and traffic conditions. Evaluation in real-life traffic situations is difficult and experimental methods are necessary where similar driving conditions can be reproduced to compare different control strategies. A traditional approach for evaluating vehicle performance, for example fuel consumption, is to use predefined driving cycles including a speed profile the vehicle should follow.