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Effective and precise torque estimation is a great opportunity to improve actual torque-based engine management strategies. Modern ECU often already implement algorithms to estimate on-board the torque that is being produced by the engine, even if very often these estimation algorithms are based on look-up tables and maps and cannot be employed for example for diagnostic purposes. The indicated torque estimation procedure presented in this paper is based on the measurement of the engine speed fluctuations, and is mainly based on two separated steps. As a first step a torsional behavior model of the powertrain configuration is developed. The engine-driveline torsional model enables to estimate the indicated torque frequency component amplitude from the corresponding component of the instantaneous engine speed fluctuation. This estimation can be performed cycle by cycle and cylinder by cylinder.

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.

The design of a complex real-time embedded system requires the specification of its functionality, the design of the hardware and software architectures, the implementation of hardware and software components and finally the system validation. The designer, starting from the specification, refines the solution trying to minimize the system cost while satisfying functional and non functional requirements. The automatic code generation from models and the introduction of the platform-based design methodology can drastically improve the design efficiency of the software partition, while maintaining acceptable the cost overhead of the final system. In this approach, both top-down and bottom-up aspects are considered and solutions are found by a meet-in-the-middle approach that couples model refinement and platform modeling.

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.

Design and optimization of intake and exhaust systems and valve timing is crucial in development of a naturally aspirated engine. Nowadays numerical simulation is a fundamental tool for this area. Unfortunately to perform an optimization of engine performance by setting even only a few parameters needs great effort in terms of time and engineering resources even with simple architecture engines. To overcome this problem the authors have developed an optimization methodology: the use of a 1_D simulation code allows one to build a neural network (NN) that characterizes engine working conditions for several input data variations (such as intake/exhaust systems and valve timing). A genetic algorithm (GA) coupled with the neural network is used to carry-out the multi-parameter optimization of engine performance.

A hydraulic accumulator used in gear selection phase of an automated manual transmission was studied to employ simulations which could predict response time of entire system. A spring-mass-damper mathematical model was created from real data and response time measured in acquisitions of a first prototype system built. The model objective was to determine values for damper coefficient and spring mass rate to be used in the design of a pair of springs with enough stiffness to achieve system response time desired. With prototype data and mathematical model developed, predictions about response time of a final system were performed and a spring rate value was determined to satisfy with response time requested. From model data, numerical structural analyses were performed in order to predict eventual final system failures due to the stiffness values involved.