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In order to detect degradation of engine oil lubricant, bench testing along with a number of diesel-powered Ford trucks were instruments and tested. The purpose of the bench testing was primarily to determine performance aspects such as repeatability, hysteresis effects and so on. Vehicle testing was conducted by designing and installing a separate oil reservoir along with a circulation system which was mounted in the vicinity of the oil pan. An innovative oil sensor was directly installed on the reservoir which can measure five (5) independent oil parameters (viscosity, density, permittivity, conductance, temperature). In addition, the concept is capable of detecting the oil level continuously during normal engine operation. The sensing system consists of an ultrasonic transducer for the oil level detection as well as a Tuning Fork mechanical resonator for the oil condition measurement.

In this paper, thermal models are developed based on experimental test data, and the physics of thermal systems. If experimental data is available, the data can be fitted to mathematical models that represent the system response to changes in its input parameters. Therefore, empirical models which are based on test data are developed. The concept of time constant is presented and applied to development of transient models. Mathematical models for component temperature changes during transient vehicle driving conditions are also presented. Mathematical models for climate control system warm up and cool-down are also discussed. The results show the significance of adopting this concept in analysis of vehicle test data, and in development of analytical models. The developed models can be applied to simulate the system or component response to variety of changes in input parameters. As a result, significant testing and simulation time can be saved during the vehicle development process.

This paper presents an evaluation of two different Vehicle to Infrastructure (V2I) applications, namely Red Light Violation Warning (RLVW) and Green Light Optimized Speed Advisory (GLOSA). The evaluation method is to first develop and use Hardware-in-the-Loop (HIL) simulator testing, followed by extension of the HIL testing to road testing using an experimental connected vehicle. The HIL simulator used in the testing is a state-of-the-art simulator that consists of the same hardware like the road side unit and traffic cabinet as is used in real intersections and allows testing of numerous different traffic and intersection geometry and timing scenarios realistically. First, the RLVW V2I algorithm is tested in the HIL simulator and then implemented in an On-Board-Unit (OBU) in our experimental vehicle and tested at real world intersections.

Vehicle to Vehicle Communication use case performance heavily relies on market penetration rate. The more vehicles support a use case, the better the customer experience. Enabling these use cases with acceptable quality on vehicles without built-in navigation systems, elaborate map matching and highly accurate sensors is challenging. This paper introduces a simulation framework to assess system performance in dependency of vehicle positioning accuracy for matching approach path traces in Decentralized Environmental Notification Messages (DENMs) in absence of navigation systems supporting map matching. DENMs are used for distributing information about hazards on the road network. A vehicle without navigation system and street map can only match its position trajectory with the trajectory carried in the DENM.

In an automotive cooling circuit, the wax melting process determines the net and time history of the energy transfer between the engine and its environment. A numerical process that gives insight into the mixing process outside the wax chamber, the wax melting process inside the wax chamber, and the effect on the poppet valve displacement will be advantageous to both the engine and automotive system design. A fully three dimensional, transient, system level simulation of an inlet controlled thermostat inside an automotive cooling circuit is undertaken in this paper. A proprietary CFD algorithm, Simerics-Sys®/PumpLinx®, is used to solve this complex problem. A two-phase model is developed in PumpLinx® to simulate the wax melting process. The hysteresis effect of the wax melting process is also considered in the simulation.

Engine downsizing, boosting, direct injection and variable valve actuation, have become industry standards for reducing CO2 emissions in current production vehicles. Because of the increasing complexity of the engine air path system and the high number of degrees of freedom for engine charge management, the design of air path control algorithms has become a difficult and time consuming process. One possibility to reduce the control development time is offered by Software-in-the-Loop (SIL) or Hardware-in-the-Loop (HIL) simulation methods. However, it is significantly challenging to identify engine air path system simulation models that offer the right balance between fidelity, mathematical complexity and computational burden for SIL or HIL implementation.

Air quenching is a common manufacturing process in automotive industry to produce high strength metal component by cooling heated parts rapidly in a short period of time. With the advancement of finite element analysis (FEA) methods, it has been possible to predict thermal residual stress by computer simulation. Previous research has shown that heat transfer coefficient (HTC) for steady air quenching process is time and temperature independent but strongly flow and geometry dependent. These findings lead to the development of enhanced HTC method by performing CFD simulation and extracting HTC information from flow field. The HTC obtained in this fashion is a continuous function over the entire surface. In current part of the research, two patching algorithms are developed to divide entire surface into patches according to HTC profile and each patch is assigned a discrete HTC value.

Fatigue analysis in the time domain using the rainflow cycle counting algorithm is considered the most accurate method for estimating damage. Dirlik's method has been found to be very accurate for damage estimation in the frequency domain. Previous studies have demonstrated the usefulness of Dirlik's method for ocean engineering and wind turbines but few have shown how well Dirlik performs in automotive applications. This study compares Dirlik's method with the rainflow cycle counting and with other frequency domain methods. The study analyzes measured data for an automotive component subjected to five test track load conditions. In addition, fourteen of Dirlik's original spectra and seven additional spectra which combine sine and random spectra are studied. It was found that Dirlik's method predicts more damage than the rainflow cycle counting method when applied to the original data used in creating the method.

In this paper, a transient thermal analysis model for Diesel fuel systems is presented. The purpose of this work is to determine the fuel temperature at various locations along the system, especially inside the tank and at the returned fuel inlet to the tank. Due to the fact that the fuel level is continuously changing during any driving condition, the fuel mass inside the tank is also continuously changing. Consequently, the fuel temperature will change even under steady driving or idle conditions, therefore, this problem should be analyzed using transient thermal analysis models. Effective thermal management requires controlling the surface temperature of the fuel tank, fuel lines and the fuel temperature at the fuel return line as well as inside the tank [1, 2]. Based on the thermal analysis results, it is possible to determine the major source of heat input at several locations of the fuel system.

Two on-line algorithms have been developed to acquire driveline component loads in terms of revolutions at torque and rainflow cycle counting matrix. These algorithms have been implemented in real-time on a standard engine controller unit and have been optimized for fast run-time and low memory requirements. The revolutions at torque algorithm is intended to count the number of driveshaft revolutions in each torque level for each gear and store the number of counts in the engine controller memory. The rainflow cycle counting algorithm is intended to count driveshaft torque cycles and to store the number of counts in a two dimensional “from-to” matrix format in the engine controller memory. The revolutions at torque histogram data and the rainflow cycle counting matrix are then downloaded from the vehicle using the data collection device. Download occurs when the vehicle is serviced at a dealership.

In today's light-weight vehicles, the strength of spot welds plays an important role in overall product integrity, reliability and customer satisfaction. Naturally, there is a need for a quick and reliable technique to inspect the quality of the welds. In the past, the primary quality control tests for detecting weld defects are the destructive chisel test and peel test [1]. The non-destructive evaluation (NDE) method currently used in industry is based on ultrasonic inspection [2, 3, 4]. The technique is not always successful in evaluating the nugget size, nor is it effective in detecting the so-called “cold” or “stick” welds. Therefore, it is necessary to develop a precise and reliable noncontact NDE method for spot welds. There have been numerous studies in predicting the weld nugget size by considering the spot-weld process [5, 6].

Auto-manufacturers are under increasing pressure to develop powertrain systems for automotive vehicles, which are more efficient regarding fuel consumption, less polluting and still keep high performance levels. Hybrid electrical vehicles (HEV) are considered the most promising technology in sight, considering a time horizon of more ore less twenty years. HEVs combine benefits of electrical vehicles, such zero emission, low noise and high torques at low velocities and advantages of conventional vehicles, such as large autonomy, great reliability and high levels of performance. This paper is focused on the major elements of an HEV powertrain: electrical motors, internal combustion engine (ICE) and batteries, which are described. The paper also presents a comparison of two possible HEV configurations: series and parallel. The mathematical model of a small hybrid vehicle is developed using software ADVISOR.

An assessment tool was developed for rollover CAE signals evaluation to assess primarily the qualities of CAE generated sensor waveforms. This is a key tool to be used to assess CAE results as to whether they can be used for algorithm calibration and identify areas for further improvement of sensor. Currently, the method is developed using error estimates on mean, peak and standard deviation. More metrics, if necessary, can be added to the assessment tool in the future. This method has been applied to various simulated signals for laboratory-based rollover test modes with rigid-body-based MADYDO models.

This paper presents the development of an analytical model that complements laboratory based experiments to provide a tool for Selective Catalyst Reduction (SCR) applications. The model calibration is based on measured data from NOx reduction performance tests as well as ammonia (NH3) adsorption/desorption tests over select SCR catalyst formulations in a laboratory flow reactor. Only base metal/zeolite SCR samples were evaluated. Limited validations are presented that show the model agrees well with vehicle data from Environmental Protection Agency Federal Test Procedure (EPA FTP) emission assessments. The model includes energy and mass balances, several different NH3 reactions with NOx, NH3 adsorption and desorption algorithms, and NH3 oxidation.

Automotive companies have invested a fortune over the last three decades developing real-time embedded control strategies and software to achieve desired functions and performance attributes. Over time, these control algorithms have matured and achieved optimum behavior. The companies have vast repositories of embedded software for a variety of control features that have been validated and deployed for production. These software functions can be reused with minimal modifications for future applications. The companies are also constantly looking for new ways to improve the productivity of the development process that may translate into lower development costs, higher quality and faster time-to-market. All companies are currently embracing Model Based Design (MBD) tools to help achieve the gains in productivity. The most cost effective approach would be to reuse the available legacy software for carry-over features while developing new features with the new MBD tools.

Using a fast-sampling valve, residual-fraction levels were determined in a 2.0L spark-ignited production engine, over varying engine operating conditions. Individual samples for each operating condition were analyzed by gas-chromatography which allowed for the determination of in-cylinder CO and CO2 levels. Through a comparison of in-cylinder measurement and exhaust data measurements, residual molar fraction (RMF) levels were determined and compared to analytical results. Analytical calculations were performed using the General Engine SIMulation (GESIM) which is a steady state quasi-dimensional engine combustion cycle simulation. Analytical RMF levels, for identical engine operating conditions, were compared to the experimental results as well as a sensitivity study on wave-dynamics and heat transfer on the analytically predicted RMF. Similarly, theoretical and experimental NOx emissions were compared and production sensitivity on RMF levels explored.

Computer Aided Engineering (CAE) has become a vital tool for product development in automotive industry. Various computer models for occupant restraint systems are developed. The models simulate the vehicle interior, restraint system, and occupants in different crash scenarios. In order to improve the efficiency during the product development process, the model quality and its predictive capabilities must be ensured. In this research, an objective model validation metric is developed to evaluate the model validity and its predictive capabilities when multiple occupant injury responses are simultaneously compared with test curves. This validation metric is based on the probabilistic principal component analysis method and Bayesian statistics approach for multivariate model assessment. It first quantifies the uncertainties in both test and simulation results, extracts key features, and then evaluates the model quality.

Wavelets are a powerful mathematical tool used to multi-resolution time-frequency decomposition of signals, in order to analyze them in different scales and obtain different aspects of the information. Despite being a relatively new tool, wavelets have being applied in several areas of human knowledge, especially in signal processing, with emphasis in encoding and compression of image, video and audio. Based on a previous successful applications (FRAZIER, 1999) together a commitment to quality results, this paper evaluates the use of the Discrete Wavelet Transform (DWT) as an compression algorithm to reduce the amount of data collected in road load signals (load history) which are used by the durability engineering teams in the automotive industry.

Brake system development and testing is spread over vehicle manufacturers, system and component suppliers. Test equipment from different sources, even resulting from different technology generations, different data analysis and report tools - comprising different and sometimes undocumented algorithms - lead to a difficult exchange and analysis of test results and, at the same time, contributes to unwanted test variability. Other studies regarding the test variability brought up that only a unified and unambiguous data format will allow a meaningful and comparative evaluation of these data and only standardization will reveal the actual reasons of test variability. The text at hand illustrates that a substantial part of test variability is caused by a misinterpretation of data and/or by the application of different algorithms.

Gliders can climb to substantial altitudes without employing any on-board energy resources but using proper piloting skills to utilize rising air currents called thermals. Recent experiments on small Unmanned Aerial Vehicles (UAVs) indicate a significant potential to increase both the flight velocity and the range of gliders by means of such maneuvers. In these experiments the velocity to approach a thermal has been recognized as a critical performance factor, and is chosen as the controlled variable. Accurate longitudinal controllers are required to track the optimal flight trajectories generated using path planning algorithms. These controllers are challenged by the presence of uncertain and time-varying aircraft dynamics, gust disturbances, and control actuator limitations.