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The present paper is about the rotational speed measurement of an automotive turbocharger, obtained starting from the analysis of acoustic emission produced by an engine, which have been acquired by a microphone placed under the vehicle hood. In the first part of the paper several upgrades to increase the overall performance of the speed extraction algorithm are presented and discussed, starting from the basic algorithm that has already demonstrated the methodology capability in a previous paper. In particular it has been considered a different signal sampling rate in order to extend the applicability of the methodology to a wider range of engines. Also a new processing procedure has been defined to increase the capability of the algorithm to tune on the frequency signal.

The use of piezoelectric cylinder pressure sensors is very popular during engine testing, but cylinder pressure information is becoming mandatory also in several on-board applications, where Low Temperature Combustion (LTC) approaches require a feedback control of combustion, due to poor combustion stability and the risk of knock or misfire. Several manufacturers showed the capability to develop solutions for cylinder pressure sensing in on-board automotive and aeronautical applications, and some of them have been patented. The most straight-forward approach seems the application of a piezo-electric washer as a replacement of the original part equipping the spark plug; the injector could also be used to transfer the cylinder pressure information to the piezoelectric quartz, in diesel or Gasoline Direct Injections (GDI) engines.

To establish a fair competition between racing vehicles is not an easy task, if different types of engine are allowed to participate (within the same class). In the Motorsports world there are several Championships where the regulations leave to the project manager substantial freedom in the vehicle-engine layout definition: The 2002 World Offshore Class I Championship (WOCC) seems to be an excellent example, since both gasoline and diesel (naturally aspirated and turbocharged) engines are admitted to race. The paper presents a power output comparison method that could be useful both for the organizers to establish a fair competition as well as for the racing engineers to decide what's the optimal layout. Since the analysis regards the maximum power, BMEP and engine speed have to be evaluated under such condition for the engines to be compared.

Knock is a non-deterministic phenomenon and its intensity is typically defined by a non-symmetrical distribution, under fixed operating conditions. A statistical approach is therefore the correct way to study knock features. Typically, intrinsically deterministic knock models need to artificially introduce Cycle-to-Cycle Variation (CCV) of relevant combustion parameters, or of cycle initial conditions, to generate different knock intensity values for a given operating condition. Their output is limited to the percentage of knocking cycles, once the user imposes an arbitrary knock intensity threshold to define the correlation between the number of knocking events and the Spark Advance (SA). In the first part of the paper, a statistical analysis of knock intensity is carried out: for different values of SA, the probability distributions of an experimental Knock Index (KI) are self-compared, and the characteristics of some percentiles are highlighted.

Specific power and efficiency of gasoline engines are influenced by factors such as compression ratio and Spark Advance (SA) regulation. These factors influence the combustion development over the crank angle: the trade-off between performance and the risk of irreversible damages is still a key element in the design of both high-performance (racing) and low-consumption engines. This paper presents a novel approach to the problem, with the objective of defining a damage-related and operating conditions-independent index. The methodology is based on the combined analysis of indicating parameters, such as Cumulated Heat Release (CHR), Indicated Mean Effective Pressure (IMEP) and 50% Mass Fraction Burned (MFB50), and typical knock detection parameters, estimated by means of the in-cylinder pressure sensor signal. Knocking combustions have several consequences, therefore they can be detected in many ways.

Knocking combustions heavily influence the efficiency of Spark Ignition engines, limiting the compression ratio and sometimes preventing the use of Maximum Brake Torque (MBT) Spark Advance (SA). A detailed analysis of knocking events can help in improving the engine performance and diagnostic strategies. An effective way is to use advanced 3D Computational Fluid Dynamics (CFD) simulation for the analysis and prediction of the combustion process. The standard 3D CFD approach based on RANS (Reynolds Averaged Navier Stokes) equations allows the analysis of the average engine cycle. However, the knocking phenomenon is heavily affected by the Cycle to Cycle Variation (CCV): the effects of CCV on knocking combustions are then taken into account, maintaining a RANS CFD approach, while representing a complex running condition, where knock intensity changes from cycle to cycle.

Combustion control is assuming a crucial role in reducing engine tailpipe emissions and maximizing performance. The number of actuations influencing the combustion is increasing, and, as a consequence, the control parameters calibrations is becoming challenging. One of the most effective factors influencing performance and efficiency is the combustion phasing: gasoline engines Electronic Control Units (ECU) manage the Spark Advance (SA) in order to set the optimal combustion phase. SA optimal values are usually determined by means of calibration procedures carried out on the test bench by changing SA values while monitoring Brake and Indicated Mean Effective Pressure (BMEP, IMEP), Brake Specific Fuel Consumption (BSFC) and pollutant emissions. The effect of SA on combustion is stochastic, due to the cycle-to-cycle variation: the analysis of mean values requires many engine cycles to be significant of the performance obtained with the given control setting.

Combustion control is one of the keys to obtain better performance and pollutants emission, both for diesel, spark ignition and HCCI engines. This paper presents a low-cost and high performance system based on commercially available hardware and software, which allows the implementation of control and diagnostic strategies based on combustions analysis, with the typical Rapid Control Prototyping (RCP) advantages (user friendly development tools, real time calibration, etc.). Information on the combustion process can be accessed by means of an indicating sensor such as an in-cylinder pressure transducer, or a ionization current measurement system, depending on the application. The signal must be sampled with a fast sampling system within a given crank angle window. It is then possible to process the input signal, in order to evaluate diagnostic or control indexes which can be calculated before the end of the same engine cycle, and finally used to correct the engine control parameters.

The mixture composition heavily influences the combustion process of Port Fuel Injection (PFI) engines. The local mixture air-index at the spark plug is closely related to combustion instabilities and the cycle-by-cycle Indicated Mean Effective Pressure (IMEP) Coefficient of Variation (CoV) well correlates with the variability of the flame kernel development. The needs of reducing the engine emissions and consumption push the engine manufactures to implement techniques providing a better control of the mixture quality in terms of homogeneity and variability. Simulating the mixture formation of a PFI engine by means of CFD techniques is a critical issue, since involved phenomena are highly heterogeneous and a two phase flow must be considered. The aim of the paper is to present a multi-cycle methodology for the simulation of the injection and the mixture formation processes of high performance PFI engine, based on the validation of all the main physical sub-models involved.

Missing combustions phenomena have been studied for a long time, in order to achieve on board diagnosis capability, due to their effect on emissions and after treatment system life. A detailed analysis of missing combustion causes can be used beyond the On Board Diagnostic (OBD) regulations observance aim, both for modeling and diagnostic purposes. The combustion taking place in a faulty cylinder right after the fault happens is usually different with respect to a standard one: both the residual gas fraction and the fuel film effect have strong influences on post-faulty combustions. Parameters used to describe these phenomena can then be evaluated analyzing the engine post-faulty behavior. The same analysis may lead to a better fault description, thus improving diagnosis performance.

The purpose of this paper is to present some innovative techniques developed for an unconventional utilization of currently standard exhaust sensors, such as HEGO, UEGO, and NOx probes. In order to comply with always more stringent legislation about pollutant emissions, intake-exhaust systems are becoming even more complex and sophisticated, especially for CI engines, often including one or two UEGO sensors and a NOx sensor, and potentially equipped with both short-route and long-route EGR. Within this context, the effort to carry out novel methods for measuring the main exhaust gas dynamic properties exploiting sensors installed for different purposes, could be useful both for control applications, such as EGR rates estimation, or cost reduction, minimizing the on-board devices number. In this work, a gray-box model for measuring the gas mass flow rate, based on standard NOx sensor operating parameters of its heating circuit, is analyzed.

This paper shows how Rapid Control Prototyping (RCP) and Computational Fluid Dynamics (CFD) techniques have been applied to design and implement an engine control system for a common rail diesel engine. The project aim is to setup a high performance engine in order to participate to the Italian Tractor Pulling Championship (Prostock category). The original engine is a John Deere 6081 Tier2 model, already equipped with a common rail system. Engine performance is substantially determined by the control system, which is in charge of limiting engine speed, boost pressure and Air to Fuel Ratio (AFR). Given that typically the information and equipment needed to change control parameters are not accessible to customers, the first step of the project has been to replace the original control system, while maintaining injectors and pumps. This solution can guarantee the best performance, but it requires time to design the new control system, both in terms of hardware and software.

The paper presents the development and real-time implementation of a combustion control system based on optimal management of multiple spark discharge events, in order to increase combustion stability, reduce pollutant emissions and fuel consumption, and avoid partial or missing combustion cycles. The proposed approach has been developed as a cost-effective solution to several combustion-related issues that affect Gasoline Direct Injection (GDI) engines during cold start and part load operation. The problem of optimizing combustion efficiency and improving its stability during such operating modes is even more critical for high performance engines, which are designed to maximize charge efficiency especially at medium-high engine speeds.

The paper presents the main results obtained by developing and critically comparing different evaporative emissions leak detection diagnostic systems. Three different leak detection methods have been analyzed and developed by using a model-based approach: depressurization, air and fuel vapor compression, and natural vacuum pressure evolution. The methods have been developed to comply with the latest OBD II requirement for 0.5 mm leak detection. Detailed grey-box models of both the system (fuel tank, connecting pipes, canister module, engine intake system) and the components needed to perform the diagnostic test (air compressor or vacuum pump) have been used to analyze in a simulation environment the critical aspects of each of the three methods, and to develop “optimal” diagnostic model-based algorithms.

This paper describes the development of a mathematical model which allows the simulation of the Internal Combustion Engine (ICE), the transmission and the vehicle dynamics of a motor vehicle equipped with a Continuously Variable Transmission (CVT) system. The aim of this work is to realize a simulation tool that is able to evaluate the performance and the operating conditions of the ICE, once it is installed on a given vehicle. Since the simulation has to be run in real-time for Hardware In the Loop (HIL) applications, a zero-dimensional (filling and emptying) model is used for modeling the cylinder thermodynamics and the intake and exhaust manifolds. The combustion is modeled by means of single zone model, with the fuel burning rate described by Wiebe functions. The gas proprieties depend on temperature and chemical composition of the gas, which are evaluated at each crank-angle.

A control oriented model of a Dual Clutch Transmission was developed for real time Hardware In the Loop (HIL) applications. The model is an innovative attempt to reproduce the fast dynamics of the actuation system maintaining a step size large enough for real time applications. The model comprehends a detailed physical description of hydraulic circuit, clutches, synchronizers and gears, and simplified vehicle and internal combustion engine sub-models; a stable real time simulation is achieved with a simplification of the model without losing physical validity. After an offline validation, the model was implemented in a HIL system and connected to the TCU (Transmission Control Unit) via two input-output boards, and to a load plate which comprehends all the actuators.

Modern turbo-charged downsized engines reach high values of specific power, causing a significant increase of the exhaust gas temperature. Such parameter plays a key role in the overall powertrain environmental impact because it strongly affects both the catalyst efficiency and the turbine durability. In fact, common techniques to properly manage the turbine inlet gas temperature are based on mixture enrichment, which causes both a steep increase in specific fuel consumption and a decrease of catalyst efficiency. At the test bench, exhaust gas temperature is typically measured using thermocouples that are not available for on-board application, and such information is processed to calibrate open-loop look-up-tables. A real-time, reliable, and accurate exhaust temperature model would then represent a strategic tool for improving the performance of the engine control system.

Multi-jet injection strategies open significant opportunities for the combustion management of the modern diesel engine. Splitting up the injection process into 5 steps facilitates the proper design of the combustion phase in order to obtain the desired torque level, whilst attempting a reduction in emissions, particularly in terms of NOx. Complex 3-D models are needed in the design stage, where components such as the injector or combustion chamber shape have to be determined. Alternatively, zero-dimensional approaches are more useful when fast interpretation of experimental data is needed and an optimization of the combustion process should be obtained based on actual data. For example, zero-dimensional models allow a quick choice of optimum control settings for each engine operating condition, avoiding the need to test all the possible combinations of engine control parameters.

Combustion phasing is crucial to achieve high performance and efficiency: for gasoline engines control variables such as Spark Advance (SA), Air-to-Fuel Ratio (AFR), Variable Valve Timing (VVT), Exhaust Gas Recirculation (EGR), Tumble Flaps (TF) can influence the way heat is released. The optimal control setting can be chosen taking into account performance indicators, such as Indicated Mean Effective Pressure (IMEP), Brake Specific Fuel Consumption (BSFC), pollutant emissions, or other indexes inherent to reliability issues, such as exhaust gas temperature, or knock intensity. Given the high number of actuations, the calibration of control parameters is becoming challenging.

Knocking combustions heavily limits the efficiency of Spark Ignition engines. The compression ratio is limited in the design stage of the engine development, letting to Spark Advance control the task of reducing the odds of abnormal combustions. A detailed analysis of knocking events can help improving engine performance and diagnosis strategies. An effective way is to use advanced 3D CFD (Computational Fluid Dynamics) simulation for the analysis and prediction of combustion performance. Standard 3D CFD approach is based on RANS (Reynolds Averaged Navier Stokes) equations and allows the analysis of the mean engine cycle. However knocking phenomenon is not deterministic and it is heavily affected by the cycle to cycle variation of engine combustions. A methodology for the evaluation of the effects of CCV (Cycle by Cycle Variability) on knocking combustions is here presented, based on both the use of Computation Fluid Dynamics (CFD) tools and experimental information.