Search Results

The recent advance in the development of various hybrid vehicle technologies comes along with the need of establishing optimal energy management strategies, in order to minimize both fuel economy and pollutant emissions, while taking into account an increasing number of state and control variables, depending on the adopted hybrid architecture. One of the objectives of this research was to establish benchmarking performance, in terms of fuel economy, for real time on-board management strategies, such as ECMS (Equivalent Consumption Minimization Strategy), whose structure has been implemented in a SIMULINK model for different hybrid vehicle concepts.

The next steps of the current European and US legislation, EURO 6c and LEV III, and the incoming new test cycles will impose more severe restrictions on pollutant emissions for Gasoline Direct Injection (GDI) engines. In particular, soot emission limits will represent a challenge for the development of this kind of engine concept, if injection and after-treatment systems costs are to be minimized at the same time. The paper illustrates the results obtained by means of a numerical and experimental approach, in terms of soot emissions and combustion stability assessment and control, especially during catalyst-heating conditions, where the main soot quantity in the test cycle is produced. A number of injector configurations has been designed by means of a CAD geometrical analysis, considering the main effects of the spray target on wall impingement.

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.

Recent and forthcoming fuel consumption reduction requirements and exhaust emissions regulations are forcing the development of innovative and particularly complex intake-engine-exhaust layouts. In the case of Spark Ignition (SI) engines, the necessity to further reduce fuel consumption has led to the adoption of direct injection systems, displacement downsizing, and challenging intake-exhaust configurations, such as multi-stage turbocharging or turbo-assist solutions. Further, the most recent turbo-GDI engines may be equipped with other fuel-reduction oriented technologies, such as Variable Valve Timing (VVT) systems, devices for actively control tumble/swirl in-cylinder flow components, and Exhaust Gas Recirculation (EGR) systems. Such degree of flexibility has a main drawback: the exponentially increasing effort required for optimal engine control calibration.

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.

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.

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.