Modelling, control and testing of internal combustion engines to minimize consumption and pollutant emissions

The objective of the PhD thesis was to research technologies and strategies to reduce fuel consumption and pollutants emission produced by internal combustion engines. In order to meet this objective my activity was focused on the research of advanced controls based on cylinder pressure feedback. These types of control strategies were studied because they present promising results in terms of engine efficiency enhancement. In the PhD dissertation two study cases are presented. The first case is relative to a control strategy to be used at the test bench for the optimisation of the spark advance calibration of motorcycle Engine. The second case is relative to a control strategy to be used directly on board of mining engines with the objective or reducing the engine consumption and correct ageing effects. In both cases the strategies proved to be effective but their implementation required the use of specific toolchains for the measure of the cylinder pressure feedback that for a matter of cost makes feasible the strategy use only for applications: • At test bench • In small-markets like large off-road engines The major bottleneck that prevents the implementation of these strategies on mass production is the cost of cylinder pressure sensor. In order to tackle this issue, during the PhD research, the development of a low-cost sensor for the estimation of cylinder pressure was studied. The prototype was a piezo-electric washer designed to replace the standard spark-plug washer or high-pressure fuel injectors gasket. From the data analysis emerged the possibility to use the piezo-electric prototype signal to evaluate with accuracy several combustion metrics compatible for the implementation of advanced control strategies in on-board applications. Overall, the research shows that advanced combustion controls are feasible and beneficial, not only at the test bench or on stationary engines, but also in mass-produced engines.

Nanostructured piezoelectric materials for the design and development of self-sensing composite materials and energy harvesting devices

The work activities reported in this PhD thesis regard the functionalization of composite materials and the realization of energy harvesting devices by using nanostructured piezoelectric materials, which can be integrated in the composite without affecting its mechanical properties. The self-sensing composite materials were fabricated by interleaving between the plies of the laminate the piezoelectric elements. The problem of negatively impacting on the mechanical properties of the hosting structure was addressed by shaping the piezoelectric materials in appropriate ways. In the case of polymeric piezoelectric materials, the electrospinning technique allowed to produce highly-porous nanofibrous membranes which can be immerged in the hosting matrix without inducing delamination risk. The flexibility of the polymers was exploited also for the production of flexible tactile sensors. The sensing performances of the specimens were evaluated also in terms of lifetime with fatigue tests. In the case of ceramic piezo-materials, the production and the interleaving of nanometric piezoelectric powder limitedly affected the impact resistance of the laminate, which showed enhanced sensing properties. In addition to this, a model was proposed to predict the piezoelectric response of the self-sensing composite materials as function of the amount of the piezo-phase within the laminate and to adapt its sensing functionalities also for quasi-static loads. Indeed, one final application of the work was to integrate the piezoelectric nanofibers in the sole of a prosthetic foot in order to detect the walking cycle, which has a period in the order of 1 second. In the end, the energy harvesting capabilities of the piezoelectric materials were investigated, with the aim to design wearable devices able to collect energy from the environment and from the body movements. The research activities focused both on the power transfer capability to an external load and the charging of an energy storage unit, like, e.g., a supercapacitor.

Sensor networks optimization and software development for Structural Health Monitoring based on ultrasonic guided waves

The Structural Health Monitoring (SHM) research area is increasingly investigated due to its high potential in reducing the maintenance costs and in ensuring the systems safety in several industrial application fields. A growing demand of new SHM systems, permanently embedded into the structures, for savings in weight and cabling, comes from the aeronautical and aerospace application fields. As consequence, the embedded electronic devices are to be wirelessly connected and battery powered. As result, a low power consumption is requested. At the same time, high performance in defects or impacts detection and localization are to be ensured to assess the structural integrity. To achieve these goals, the design paradigms can be changed together with the associate signal processing. The present thesis proposes design strategies and unconventional solutions, suitable both for real-time monitoring and periodic inspections, relying on piezo-transducers and Ultrasonic Guided Waves. In the first context, arrays of closely located sensors were designed, according to appropriate optimality criteria, by exploiting sensors re-shaping and optimal positioning, to achieve improved damages/impacts localisation performance in noisy environments. An additional sensor re-shaping procedure was developed to tackle another well-known issue which arises in realistic scenario, namely the reverberation. A novel sensor, able to filter undesired mechanical boundaries reflections, was validated via simulations based on the Green's functions formalism and FEM. In the active SHM context, a novel design methodology was used to develop a single transducer, called Spectrum-Scanning Acoustic Transducer, to actively inspect a structure. It can estimate the number of defects and their distances with an accuracy of 2[cm]. It can also estimate the damage angular coordinate with an equivalent mainlobe aperture of 8[deg], when a 24[cm] radial gap between two defects is ensured. A suitable signal processing was developed in order to limit the computational cost, allowing its use with embedded electronic devices.