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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.

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.

The acoustic characteristics of a hybrid silencer consisting of two dissipative chambers and a Helmholtz resonator are investigated first computationally and experimentally. Complex wave number and characteristic impedance are used for the dissipative chambers to account for the wave propagation through absorbing material. Three-dimensional boundary element method (BEM) is employed to predict the transmission loss in the absence of mean flow and the predictions are compared with the experimental results obtained from an impedance tube setup. Noting that the long connecting tube between acoustic elements may reduce the transmission loss near the resonance frequency, two alternative hybrid silencers with short connecting tubes are also investigated by BEM. The present study shows the effectiveness of hybrid silencers over a wide frequency range and demonstrates the importance of understanding each acoustic element, as well as their interaction in designing silencers.

Transmission error has long been identified to be the main exciter of gear whine noise. This research effort seeks to investigate the mechanisms and principal controlling factors that affect the actual noise generation from a typical gearbox housing due to transmission error excitations. The insight gained is expected to help in identifying possible noise control procedures in typical gearing applications. The example gearbox of this paper is an aircraft auxiliary-drive idler gearbox run at low load so that transmission error is the primary mesh excitation. A limited set of dynamic noise and vibration data are collected in transient speed run-ups. A contact-mechanics gear-tooth model is used to predict the static transmission error at each mesh. A finite-element model of the shafting that incorporates complex shaft and bearing data is used to predict the shaft dynamics with the static transmission error at the gear mesh(es) as the sole excitation.

The engine start-up process introduces speed-dependent transient vibration problems in ground vehicle drivelines as the torsional system passes through the critical speeds during the acceleration process. Accordingly, a numerical study is proposed to gain more insights about this transient vibration issue, and the focus is on nonlinear analysis. First, a new nonlinear model of a multi-staged clutch damper is developed and validated by a transient experiment. Second, a simplified nonlinear torsional oscillator model with the multi-staged clutch damper, representing the low frequency dynamics of a typical vehicle driveline, is developed. The flywheel velocity measured during the typical engine start-up process is utilized as an excitation. The envelope function of the speed-dependent response amplification is estimated via the Hilbert transform technique. Finally, the envelope function is effectively utilized to examine the effect of multi-staged clutch damper properties.

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.

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.

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.

The platooning of connected automated vehicles (CAV) possesses the significant potential of reducing energy consumption in the Intelligent Transportation System (ITS). Moreover, with the rapid development of eco-driving technology, vehicle platooning can further enhance the fuel efficiency by optimizing the efficiency of the powertrain. Since road grade is a main factor that affects the energy consumption of a vehicle, the estimation of the road grade with high accuracy is the key factor for a connected vehicle platoon to optimize energy consumption using vehicle-to-vehicle (V2V) communication. Commonly, the road grade is quantified by single consumer grade global positioning system (GPS) with the geodetic height data which is rough and in the meter-level, increasing the difficulty of precisely estimating the road grade.

A prototype hybrid exhaust silencing system consisting of dissipative and reactive components is designed based on the boundary element method (BEM) with a specific emphasis on its acoustic performance as evaluated relative to a production system. The outer dimensions of the prototype system are comparable to its production counterpart, which has two silencers connected by a pipe. The predicted transmission loss by BEM for the prototype is compared with the experimental results in an impedance tube for both the prototype and production hardware, providing a design guidance for the former. The sound pressure levels measured at the tailpipe exit during the engine ramp-up experiments in a dynamometer laboratory are presented to compare the two systems, providing the final assessment.

A multi-chamber silencer is designed by a computational approach to suppress the turbocharger whoosh noise downstream of a compressor in an engine intake system. Due to the significant levels and the broadband nature of the source spanning over 1.5 – 3.5 kHz, three Helmholtz resonators are implemented in series. Each resonator consists of a chamber and a number of slots, which can be modeled as a cavity and neck, respectively. Their target resonance frequencies are tuned using Boundary Element Method to achieve an effective noise reduction over the entire frequency range of interest. The predicted transmission loss of the silencer is then compared with the experimental results from a prototype in an impedance tube setup. In view of the presence of rapid grazing flow, these silencers may be susceptible to whistle-noise generation. Hence, the prototype is also examined on a flow bench at varying flow rates to assess such flow-acoustic coupling.

Prediction of power efficiency of gear boxes has become an increasingly important research topic since fuel economy requirements for passenger vehicles are more stringent, due to not only fuel cost but also environmental regulations. Under this circumstance, the automotive industry is dedicatedly focusing on developing a highly efficient gear box. Thus, the analysis of power efficiency of gear box should be performed to have a transmission that is highly efficient as much as possible at the beginning of design stage. In this study, a program is developed to analyze the efficiency of an entire gearbox, considering all components’ losses such as gear mesh, wet clutches, bearings, oil pump and so on. The analytical models are based on the formulations of each component power loss model which has been developed and published in many existing papers. The program includes power flow analysis of both a parallel gear-train and a planetary gear-train.

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.

Electronic closed loop control of automatic transmission functions can potentially benefit from the use of quantitative models of transmission response in a form compatible with controller design procedures. Transmission dynamic response during gear shifts of a discrete-ratio transmission is nonlinear. Procedures for developing linearized dynamic models are applied to the simulation of the nonlinear model of a representative power train during the inertia phase of a shift. The frequency responses for the resulting linear models are examined, and their implications for controller design are noted.

It is well-known that the hydrodynamic torque converter plays a major role in the transient study of power train systems since it has a great influence on the transient characteristics of a vehicle during gear shifting as well as vehicle launching. To predict accurately the vehicle characteristics, detailed analysis of the hydrodynamic torque converter is required. However, even with the development of a nonlinear dynamic model for the torque converter based on Hrovat and Tobler's paper (1985) is available, it is imperative to calculate both torques from impeller and turbine in order to utilize the dynamic model since it takes torque as an input [3]. In order to obtain the information about necessary but unmeasurable variables, nonlinear model-based estimator is developed using already available and measurable speeds data of impeller and turbine. The hydrodynamic torque converter model includes all necessary dynamics, namely, hydraulic as well as mechanical dynamics.

Many automotive components and sub-systems require viscoelastic damping treatments to control noise and vibration characteristics. To aid the dynamic design process, new approaches are needed for modeling of partial damping treatments and characterization of the overall dynamic behavior. The analytical component of the design process is illustrated via the transmission casing cover, along with supporting experiments. First, the vibration response of production casing plates is examined, with and without the constrained layer treatment. A modified flat plate is employed along with a generic housing that provides the realistic boundary conditions for subsequent work. A simplified analytical damping model for constrained viscoelastic layer damping is suggested based on assumed modal functions. Using the analytical model, design guidelines in terms of optimal patch shapes and locations are suggested.

The study emphasizes transitioning school buses from diesel to electric to mitigate their environmental impact, addressing challenges like limited driving range through predictive models. This research introduces a comprehensive control-oriented model for estimating auxiliary loads in electric school buses. It begins by developing a transient thermal model capturing cabin behavior, divided into passenger and driver zones. Integrated with a control-oriented HVAC model, it estimates heating and cooling loads for desired cabin temperatures under various conditions. Real-world operational data from school bus specifications enhance the model’s practicality. The models are calibrated using experimental cabin-HVAC data, resulting in a remarkable overall Root Mean Square Error (RMSE) of 2.35°C and 1.88°C between experimental and simulated cabin temperatures.

The EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes. This is made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 51 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the fabrication and control implementation process followed by the Ohio State team during Year 2 of the competition. The fabrication process includes finalizing designs based on identified requirements, building and assembling components, and performing extensive validation testing on the mechanical, electrical and control systems.