The engine fuel control system plays a crucial role in engine performance and fuel economy. Fuel control, in traditional engine control systems, is carried out by means of sensor-based control methods, which correct the fuel flow rate through correlations or scheduled parameters in order to reduce the error between a measured parameter and its desired value. In the presence of component degradation, however, the relationship between the engine measurable parameters and performance may lead to an increase in the control error. In this research, linear models for advanced control systems and for direct fuel control in the presence of components degradation are proposed, with the main objective being to directly predict and correct fuel consumption in the presence of degradation instead of adopting measurable parameters. Two techniques were adopted for model linearization: Small Perturbation and System Identification. Results showed that both models are characterized by high accuracy in predicting the output engine variables, with the mean errors between model prediction and data below 1%. The maximum errors, recorded for shaft power, were about 6% for Small Perturbation and lower than 3% for System Identification. A simple correlation between engine performance and components degradation was also demonstrated; in particular, the achieved results allow one to conclude that the Small Perturbation approach is the best candidate for controller development when a prediction of components degradation is included.

The aim of the paper is the techno-economic analysis of innovative integrated combined heat and power (CHP) systems for the exploitation of different renewable sources in the residential sector. To this purpose, a biofuel-driven organic Rankine cycle (ORC) is combined with a wind turbine, a photovoltaic system and an auxiliary boiler. The subsystems work in parallel to satisfy the electric and heat demand of final users: a block of 40 dwellings in a smart community. A 12.6 kW_el ORC is selected according to a thermal-driven strategy, while wind and solar subsystems are introduced to increase the global system efficiency and the electric self-consumption. The ORC can be switched-off or operated at partial load when solar and/or wind sources are significant. A multi-variable optimization has been carried out to find the proper size of the wind turbine and photovoltaic subsystems and to define the suitable operating strategy. To this purpose, several production wind turbines (1.0–60.0 kW_el) and photovoltaic units (0.3–63.0 kW_el) have been considered with the aim of finding the optimal trade-off between the maximum electric self-consumption and the minimum payback period and electric surplus. The multi-objective optimization suggests the integration of 12.6 kW_el ORC with 10 kW_el wind turbine and 6.3 kW_el photovoltaic subsystem. The investigation demonstrates that the proposed multi-source integrated system offers a viable solution for smart-communities and distributed energy production with a significant improvement in the global system efficiency (+7.5%) and self-consumption (+15.0%) compared to the sole ORC apparatus.

Improvements in internal combustion engine efficiency can be achieved with proper thermal management. In this work, a simulation tool for the preliminary analysis of the engine cooling control is developed and a model-based controller, which enforces the coolant flow rate by means of an electrically driven pump is presented. The controller optimizes the coolant flow rate under each engine operating condition to guarantee that the engine temperatures and the coolant boiling levels are kept inside prescribed constraints, which guarantees efficient and safe engine operation. The methodology is validated at the experimental test rig. Several control strategies are analyzed during a standard homologation cycle and a comparison of the proposed methodology and the adoption of the standard belt-driven pump is provided. The results show that, according to the control strategy requirements, a fuel consumption reduction of up to about 8% with respect to the traditional cooling system can be achieved over a whole driving cycle. This proves that the proposed methodology is a useful tool for appropriately cooling the engine under the whole range of possible operating conditions.