Virtual Calibration of CO2 and Pollutant Emissions of a High-Performance PHEV using Model-in-the-Loop Methodology

The study analyses the calibration process of a newly developed high-performance plug-in hybrid electric passenger car powertrain. The complexity of modern powertrains and the more and more restrictive regulations regarding pollutant emissions are the primary challenges for the calibration of a vehicle’s powertrain. In addition, the managers of OEM need to know as earlier as possible if the vehicle under development will meet the target technical features (emission included). This leads to the necessity for advanced calibration methodologies, in order to keep the development of the powertrain robust, time and cost effective. The suggested solution is the virtual calibration, that allows the tuning of control functions of a powertrain before having it built. The aim of this study is to calibrate virtually the hybrid control unit functions in order to optimize the pollutant emissions and the fuel consumption. Starting from the model of the conventional vehicle, the powertrain is then hybridized and integrated with emissions and aftertreatments models. After its validation, the hybrid control unit strategies are optimized using the Model-in-the-Loop testing methodology. The calibration activities will proceed thanks to the implementation of a Hardware-in-the-Loop environment, that will allow to test and calibrate the Engine and Transmission control units effectively, besides in a time and cost saving manner.

Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

Mitigazione sequestro e stoccaggio di diossido di carbonio

The main objective of my thesis was the technical-economic feasibility of a system of electricity generation integrated with CCS. The policy framework for development processing is part of the recent attention that at the political level has been directed towards the use of CCS technologies with the aim of addressing the problems of actual climate change. Several technological options have been proposed to stabilize and reduce the atmospheric concentrations of carbon dioxide (CO2) among which, the most promising for IPPC (Intergovernmental Panel on Climate Change)are the CCS technologies (Carbon Capture and Storage & Carbon Capture and Sequestration). The remedy proposed for large stationary CO2 sources as thermoelectric power plants is to separate the flue gas capturing CO2 and to store it into deep subsurface geological formations (more than 800 meters of depth). In order to support the identification of potential CO2 storage reservoirs in Italy and in Europe by Geo Capacity(an European database) new studies are developing. From the various literature data analyzed shows that most of the CO2 emitted from large stationary sources comes from the processes of electricity generation (78% of total emissions) and from (about 60%) those using coal especially. The CCS have the objective of return "to the sender" , the ground, the carbon in oxidized form (CO2) after it has been burned by man starting from its reduced form (CH4, oil and coal), then the carbon dioxide is not a "pollutant" if injected into the subsurface, CO2 is an acid reagent that interacts with the rock, with underground fluid and the characteristics of the host rock. The results showed that the CCS technology are very urgent, because unfortunately there are too many industrial sources of CO2 in assets (power plants, refineries, cement plants, steel mills) in the world who are carrying too quickly the CO2 atmospheric concentration levels to values that aren't acceptable for our dear planet.