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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 more virtual product development is integrated into the mass-production development process and overall development times are shortened, efficient intake-port design requires closer cooperation between design, simulation and test engineers. Doppler Global Velocimetry (DGV) has become an important link in the overall intake-port development process as it provides 3D-vector fields of flow velocity. Hence, it can be used to make direct comparisons with 3D-CFD-simulation results. The present paper describes the hardware-assisted inlet port development process for diesel engines, the cooperation among port design, 3D-CFD-simulation with the creation of alternative geometries and DGV flow-measurement of preferred variants with their capability of checking and improving simulation results.

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.

Nowadays, an automotive DI Diesel engine is demanded to provide an adequate power output together with limit-complying NOx and soot emissions so that the development of a specific combustion concept is the result of a trade-off between conflicting objectives. In other words, the development of a low-emission DI diesel combustion concept could be mathematically represented as a multi-objective optimization problem. In recent years, genetic algorithm and CFD simulations were successfully applied to this kind of problem. However, combining GA optimization with actual CFD-3D combustion simulations can be too onerous since a large number of simulations is usually required, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes.

Steer-by-wire and other “by-wire” systems (as defined in the paper) offer many passive and active safety advantages. To help ensure these advantages are achieved, a comprehensive system-safety process should be followed. In this paper, we review standard elements of system safety processes that are widely applied in several industries and describe the main elements of our proposed analysis process for by-wire systems. The process steps include: (i) creating a program plan to act as a blueprint for the process, (ii) performing a variety of hazard analysis and risk assessment tasks as specified in the program plan, (iii) designing and verifying a set of hazard controls that help mitigate risk, and (iv) summarizing the findings. Vehicle manufacturers and suppliers need to work together to create and follow such a process. A distinguishing feature of the process is the explicit linking of hazard controls to the hazards they cover, permitting coverage-based risk assessment.

Increasing emissions regulations, diagnostics capability, and other demands in vehicle refinement, have led to the need for increasingly complex engine control systems. These demands have led to in-cylinder combustion control, especially for the diesel engine. Diesel engine combustion relies heavily on the auto-ignition process. Therefore accurate control of this process is important and will become even more important for HCCI-engines. This paper discusses the configuration of a diesel engine for in-cylinder combustion control. It describes the digital evaluation of the cylinder pressure signal and the computation of the physical parameters necessary for proper combustion analysis, along with methods for using the calculated combustion parameter for engine control. The paper demonstrates the advantages of electronic engine control combined with in-cylinder pressure information. The paper also addresses some of the future challenges of engine control.

In order to satisfy environmental regulations while maintaining strong performance and excellent fuel economy, advanced diesel engines are employing sophisticated air breathing systems. These include high pressure and low pressure EGR (Hybrid EGR), intake and exhaust throttling, and variable turbine geometry systems. In order to optimize the performance of these sub-systems, system level controls are necessary. This paper presents the design, benefits and test results of a model-based air system controller applied to an automotive diesel engine.

Compression-ignited engines are still considered the most efficient and reliable technology for automotive applications. However, current and future emission regulations, which severely limit the production of NOx, particulate matter and CO2, hinder the use of diesel-like fuels. As a matter of fact, the spontaneous ignition of directly-injected Diesel leads to a combustion process that is heterogeneous by nature, therefore characterized by the simultaneous production of particulate matter and NOx. In this scenario, several innovative combustion techniques have been investigated over the past years, the goal being to benefit from the high thermal efficiency of compression-ignited engines, which results primarily from high Compression Ratio and lean and unthrottled operation, while simultaneously mitigating the amount of pollutant emissions.

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.

With new legislation and federal regulation for vehicle emission levels, automotive and truck manufacturers have been prompted to focus on emission control technologies that limit the level of exhaust pollutants. One of the primary pollutants, especially from diesel engines, is oxides of nitrogen (NOx). One possible solution to this pollution challenge is to design a more efficient internal combustion engine, which would require better engine operating parameter controls. However, there are limitations associated with such tight engine management. This need has led researchers and engineers to focus on the development of exhaust aftertreatment devices that will reduce NOx emissions with current diesel engines. An optimum aftertreatment device must be unaffected by exhaust-gas impurity poisoning such as sulfur products, and must have minimal impact on vehicle operations and fuel economy.

A practical Gasoline Compression Ignition (GCI) concept is presented that works on standard European 95 RON E10 gasoline over the whole speed/load range. A spark is employed to assist the gasoline autoignition at low loads; this avoids the requirement of a complex cam profile to control the local mixture temperature for reliable autoignition. The combustion phasing is controlled by the injection pattern and timing, and a sufficient degree of stratification is needed to control the maximum rate of pressure rise and prevent knock. With active control of the swirl level, the combustion system is found to be relatively robust against variability in charge motion, and subtle differences in fuel reactivity. Results show that the new concept can achieve very low fuel consumption over a significant portion of the speed/load map, equivalent to diesel efficiency. The efficiency is worse than an equivalent diesel engine only at low load where the combustion assistance operates.

Large Eddy Simulation (LES) represents nowadays one of the most promising techniques for the evaluation of the dynamics and evolution of turbulent structures characterizing internal combustion engines (ICE). In the present paper, subdivided into two parts, the capabilities of the open-source CFD code OpenFOAM® v2.3.0 are assessed in order to evaluate its suitability for engine cold flow LES analyses. Firstly, the code dissipative attitude is evaluated through an inviscid vortex convection test to ensure that the levels of numerical dissipation are compatible with LES needs. Quality and completeness estimators for LES simulations are then proposed. In particular the Pope M parameter is used as a LES completeness indicator while the LSR parameter provides useful insights far calibrating the grid density. Other parameters such as the two-grid LESIQk index are also discussed.

One of the most evident trends in automotive sector is miniaturization. It is related to considerable benefits due to the potential of mass reduction, cost reduction and efficiency improvement. It involves many different automobile components and most of them are facing challenges to achieve the targets defined by car makers and final consumers. Specifically for wiring harness, it seems to be many manufacturing and process challenges to be surpassed in order to fully perceive the benefits expected with miniaturization, internally and externally. So this article aims to present an overview of literature as well as reporting of experts on this issue mentioning some of the challenges that global automotive wiring harness manufacturers are facing. Subjects as assembly automation, terminal connection and small gauge cables are discussed in the article and also a general overview of how those problems are being addressed in order to meet customer requirements.

Battery simulation by a DSP-controlled high current power supply is used to improve repeatability and comparability of starting tests, especially at low temperatures. The simulator's algorithm calculates the internal resistance of the battery by a timely constant resistor and a variable resistor representing the actual discharge history. The output voltage of the simulator is set as a function of internal resistor and load current with temperature and state of charge as setup parameter. The simulator was evaluated in cold start testing in comparison to real batteries. As a result, batteries are simulated with high repeatability. Deviations to real battery behavior are in the range of test to test deviations using real batteries.

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.

This paper describes the technique of in-cylinder ionization sensing in a common rail diesel engine. The technology detects in real time, the start of combustion for both pilot and main combustion enabling the fuel control strategy to change from open to closed loop, thus, maintaining the desired start of combustion for all speeds and loads. Additionally, the ionization sensing enables the ECM to truly correct for changes in ignition delays caused by as an example a change in fuel cetane number or in air, fuel and engine temperature. The conclusions are that ionization sensing improves the ability to control a diesel engine and is a feasible technology for production vehicles.

A detailed analysis of knocking events can help improving engine performance and diagnosis strategies. The paper aim is a better understanding of the phenomena involved in knocking combustions through the combination of CFD and signals analysis tools. CFD simulations have been used in order to reproduce knock effect on the in-cylinder pressure trace. In fact, the in-cylinder pressure signal holds information about waves propagation and heat losses: for the sake of the diagnosis it is important to relate knock severity to knock indexes values. For this purpose, a CFD model has been implemented, able to predict the combustion evolution with respect to Spark Advance, from non-knocking up to heavy knocking conditions. The CFD model validation phase is crucial for a correct representation of both regular and knocking combustions: the operation has been carried out by means of an accurate statistical analysis of experimental in-cylinder pressure data.

The continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at combustion control improvement. Nowadays, performing an efficient combustion control is crucial for drivability improvement, efficiency increase and pollutant emissions reduction. These aspects are even more crucial when innovative combustions (such as LTC or RCCI) are performed, due to the high instability and the high sensitivity with respect to the injection parameters that are associated to this kind of combustion. Aging of all the components involved in the mixture preparation and combustion processes is another aspect particularly challenging, since not all the calibrations developed in the setup phase of a combustion control system may still be valid during engine life.

The pressure of the combustion gas in a diesel engine is higher than that in a gasoline engine, so the cylinder head gasket that seals the combustion chamber is exposed to a severe environment. The sealability of the gaskets is affected not only by the gasket specifications, but also by the cylinder head, cylinder block, and the head bolts that clamp them. Consequently, in order to improve the performance of these gaskets, it is essential to enhance their material characteristics. Because the necessary characteristics of a gasket material are high strength and high fatigue strength, methods of realizing these enhancements were studied, and a new material was developed. It was confirmed that a gasket made using the newly developed material withstood high combustion pressure, and the gasket was used in a high performance diesel engine.

This work focuses on the development and validation of a data-driven model capable of predicting the maximum in-cylinder pressure during the operation of an internal combustion engine, with the least possible computational effort. The model is based on two parameters, one that represents engine load and another one the combustion phase. Experimental data from four different gasoline engines, two turbocharged Gasoline Direct Injection Spark Ignition, a Naturally Aspirated SI and a Gasoline Compression Ignition engine, was used to calibrate and validate the model. Some of these engines were equipped with technologies such as Low-Pressure Exhaust Gas Recirculation and Water Injection or a compression ignition type of combustion in the case of the GCI engine. A vast amount of engine points were explored in order to cover as much as possible of the operating range when considering automotive applications and thus confirming the broad validity of the model.