1,721,126 research outputs found
A Stochastic Approach for the Optimization of Open-Loop Engine Control System, Fifth International Conference on Stochastic programming
No full textThe operation of sensors and actuators in engine control systems is always affected by errors, which are stochastic in nature. In this paper it is shown that, because of the non-linear interactions between engine performance and control laws in an open-loop engine control system, these errors can give rise to unexpected deviations of control variables, fuel consumption and emissions from the optimal values, which are not predictable in an elementary way. A model for vehicle performance evaluation on a driving cycle is presented, which provides the expected values of fuel consumption and emissions in the case of stochastic errors in sensors and actuators, utilizing only steady-state engine data. The stochastic model is utilized to obtain the optimal control laws; the resultant non-linear constrained minimization problem is solved by an Augmented Lagrangian approach, using a Quasi-Newton technique. The results of the stochastic optimization analysis indicate that significant reductions in performance degradation may be achieved with respect to the solutions provided by the classical deterministic approach
Control Oriented Modeling of Solid Oxide Fuel Cell Auxiliary Power Unit for Transportation Applications
No full textDevelopment of Modeling Tools for Optimal Design, Control and Diagnosis of Solid Oxide Fuel Cell APUs
No full textOptimization of Spark Ignition Engines with Stochastic Effects in Sensors and Actuators
No full textA dynamic model of a vehicle equipped with an electronic controlled spark ignition engine is presented. The model is used to simulate and optimize control strategies in transient conditions, both in case of deterministic or stochastic control system operation. Fuel consumption and emissions are evaluated starting from steady-state experimental data, considering also the effects on emissions of cylinder wall temperatures unsteadiness. The following dynamic phenomena are described in the model: unsteady air flow in the intake manifold, evaluated by a filling and emptying approach; two phases fuel flow, considering fuel evaporation, transport and deposition on walls; unsteady thermal flow between combustion chamber walls and cooling system. The model, characterized by limited computational time, is employed both in simulation and optimization mode to study control strategies for injection timing and spark advance, to compensate for mixture strength excursions and to improve dynamic performance, also considering stochastic effects exerted by random errors in sensors and actuators on air-fuel ratio and spark advance variance
Experimental validation of a dynamic model for mixture formation in a multi-point injection SI engine
No full textA mean value dynamic model for spark ignition engines with electronic control systems is presented, for the prediction of fuel consumption and emissions during driving cycles, considering air and fuel flow dynamics in the intake manifold and unsteady cylinder wall temperature effects on exhaust emissions. The major results obtained on mixture strength excursions in transient operation and on the possibility of designing model-based compensation strategies are reviewed, as well as the results of optimization analysis for both deterministic and stochastic cases. The results of an experimental investigation on a multi-point injection engine are presented, in order to validate air and fuel flow sub-models, using a step response technique for throttle opening and injection time. For the air model, based on a mean value filling and emptying approach, a good agreement between predicted and measured data is obtained. A least square technique has been used to identify the parameters of the fuel submodel, which predicts the observed values with a good accuracy, consistent with the objectives of the whole engine dynamic model
An integrated mathematical tool aimed at developing highly performing and cost-effective fuel cell hybrid vehicles
No full textAn integrated mathematical tool is presented to simultaneously design powertrain and control strategies for PEM fuel cell hybrid vehicles. Such an activity is motivated by the positive impact of car electrification on transportation related GHG emissions, and by the potential of hydrogen as an intensive energy carrier to avoid heavy battery packs, as required for pure electric cars. Moreover, the availability of reliable and comprehensive mathematical tools is recognized as a key to develop cost effective and highly performing innovative powertrains.
A database of hybridizing devices' costs and weights is developed and exploited in conjunction with a weight model to size the powertrain as a function of degree of hybridization. In parallel, a versatile heuristic control strategy is proposed to easily adapt control rules to different powertrains. Then, both the weight model and the heuristic control strategy are embedded into an optimization procedure to determine the most convenient PEM fuel cell hybrid vehicle configuration.
The methodology is tested for a fuel cell hybrid shuttle, whose hydrogen feeding is guaranteed by a photovoltaic on-site generation system. Such a case study not only is suitable to assess the proposed optimization procedure, but also serves at indicating the most promising short-term applications of fuel cell hybrid vehicles
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