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In the field of passenger car engines, recent research advances have proven the effectiveness of downsized, turbocharged and direct injection concepts, applied to gasoline combustion systems, to reduce the overall fuel consumption while respecting particularly stringent exhaust emissions limits. Knock and turbocharger control are two of the most critical factors that influence the achievement of maximum efficiency and satisfactory drivability, for this new generation of engines. The sound emitted from an engine encloses many information related to its operating condition. In particular, the turbocharger whistle and the knock clink are unmistakable sounds. This paper presents the development of real-time control functions, based on direct measurement of the engine acoustic emission, captured by an innovative and low cost acoustic sensor, implemented on a platform suitable for on-board application.

The most recent European regulations for two- and three-wheelers (Euro 5) are imposing an enhanced combustion control in motorcycle engines to respect tighter emission limits, and Air-Fuel Ratio (AFR) closed-loop control has become a key function of the engine management system also for this type of applications. In a multi-cylinder engine, typically only one oxygen sensor is installed on each bank, so that the mean AFR of two or more cylinders rather than the single cylinder one is actually controlled. The installation of one sensor per cylinder is normally avoided due to cost, layout and reliability issues. In the last years, several studies were presented to demonstrate the feasibility of an individual AFR controller based on a single sensor. These solutions are based on the mathematical modelling of the engine air path dynamics, or on the frequency analysis of the lambda probe signal.

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 presents the experimental work and the results obtained from the implementation of a transient fuel compensation algorithm for the 6.0-liter V12 high-performance engine that equips the Lamborghini Diablo vehicles. This activity has been carried out as part of an effort aimed at the optimization of the entire fuel injection control system. In the first part of the paper the tests for fuel film compensator identification are presented and discussed. In this phase the experimental work has been conducted in the test cell. An automatic calibration algorithm was developed to identify the well-known fuel film model X and τ parameters, so as to define their maps as a function of engine speed and intake manifold pressure. The influence of engine coolant temperature has been investigated separately; it will be soon presented together with the air dynamics compensation algorithm. In the second part of the paper, the performance of the fuel dynamics compensation algorithm is analyzed.

The paper presents the application of signal processing algorithms to racing engines acoustic emission signals. The proposed methodology has shown to be effective in extracting from such signals information related to the main powertrain performance parameters, such as engine speed, gear ratios and driver's strategy. The objective of the paper is to compare performance parameters of racing engines that have participated in two different Championships, FIA Formula One World Championship (Formula 1) and CART Champ Car Series (CART). The comparison is quite interesting, since the two formulas differ not only in terms of regulations (and therefore in terms of admissible powertrain layouts), but also in terms of circuits where the races take place. For example, ovals are quite common in CART, and that is not the case of Formula 1: This fact is reflected in the different way the engine and the gearbox are operated during the race.

The paper presents an original review and extension of existing mathematical models for on-line residual gas fraction estimation. The resulting model has first of all been extended to take into account also the presence of externally recirculated exhaust gas (external EGR), and then critically analyzed to highlight the importance of a correct Intake Valve Opening and Exhaust Valve Closing effective position identification. As shown in the paper, such quantities may be evaluated by using experimental data, either acquired in the test-cell or on a valve flow bench. The main objective is to obtain a simple and reliable model (that could be run in real time within the engine control unit) also in presence of Variable Valve Timing (VVT, both on intake and exhaust valves) and external Exhaust Gas Recirculation (EGR) systems.

Dual Mass Flywheel (DMF) systems are today widely adopted in compression ignition automotive powertrains, due to the well-known positive effects on vehicle drivability and fuel consumption. This work deals with the analysis of undesirable effects that the installation of a DMF may cause to engine and transmission dynamics, with the objective of understanding the causes and of determining possible solutions to be adopted. The main results of an experimental and simulation analysis, focused on the rotational dynamics of a powertrain equipped with a DMF system, are presented in the paper. A mathematical model of the physical system has been developed, validated, and used to investigate, in a simulation environment, the anomalous behavior of the powertrain that had been experimentally observed under specific conditions. Particular attention has been devoted to two aspects that are considered critical: engine cranking phase; interactions between powertrain dynamics and idle speed control.

Due to the recent anti-pollution policies, the performance increase in Spark Ignition (SI) engines is currently under the focus of automotive manufacturers. This trend drives control systems designers to investigate accurate solutions and build more sophisticated algorithms to increase the efficiency of this kind of engines. The development of a control strategy is composed of several phases and steps, and the first part of such process is typically spent in defining and investigating the logic of the strategy. During this phase it is often useful to have a light engine simulator, which allows to have robust synthetic combustion data with a low calibration and computational effort. In the first part of this paper, a description of the control-oriented ANalytical Engine SIMulator (ANESIM) is carried out.

Water Injection (WI) has become a key technology for increasing combustion efficiency in modern GDI turbocharged engines. In fact, the addition of water mitigates significantly the occurrence of knock, reduces exhaust gas temperatures, and opens the possibility to reach optimum heat release phasing even at high load. This work presents the latest development of a model-based WI controller, and its experimental validation on a GDI TC engine. The controller is based on a novel approach that involves an analytic combustion model to define the spark advance (SA) required to reach a combustion phase target, considering injected water mass effects. The calibration and experimental validation of the proposed controller is shown in detail in the paper.

This paper presents an optimization algorithm, based on discrete dynamic programming, that aims to find the optimal control inputs both for energy and thermal management control strategies of a Plug-in Hybrid Electric Vehicle, in order to minimize the energy consumption over a given driving mission. The chosen vehicle has a complex P1-P4 architecture, with two electrical machines on the front axle and an additional one directly coupled with the engine, on the rear axle. In the first section, the algorithm structure is presented, including the cost-function definition, the disturbances, the state variables and the control variables chosen for the optimal control problem formulation. The second section reports the simplified quasi-static analytical model of the powertrain, which has been used for backward optimization. For this purpose, only the vehicle longitudinal dynamics have been considered.

During the development of an Internal Combustion Engine-based powertrain, traditional procedures for control strategies calibration and validation produce huge amount of data, that can be used to develop innovative data-driven applications, such as emission virtual sensing. One of the main criticalities is related to the data quality, that cannot be easily assessed for such a big amount of data. This work focuses on an emission modeling activity, using an enhanced Light Gradient Boosting Regressor and a dedicated data pre-processing pipeline to improve data quality. First thing, a software tool is developed to access a database containing data coming from emissions tests. The tool performs a data cleaning procedure to exclude corrupted data or invalid parts of the test. Moreover, it automatically tunes model hyperparameters, it chooses the best set of features, and it validates the procedure by comparing the estimation and the experimental measurement.