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.

Design of an innovative electric vehicle simulator for Charging Systems' End-of-Line Testing

The trend related to the turnover of internal combustion engine vehicles with EVs goes by the name of electrification. The push electrification experienced in the last decade is linked to the still ongoing evolution in power electronics technology for charging systems. This is the reason why an evolution in testing strategies and testing equipment is crucial too. The project this dissertation is based on concerns the investigation of a new EV simulator design. that optimizes the structure of the testing equipment used by the company who commissioned this work. Project requirements can be summarized in the following two points: space occupation reduction and parallel charging implementation. Some components were completely redesigned, and others were substituted with equivalent ones that could perform the same tasks. In this way it was possible to reduce the space occupation of the simulator, as well as to increase the efficiency of the testing device. Moreover, the possibility of conjugating different charging simulations could be investigated by parallelly launching two testing procedures on a unique machine, properly predisposed for supporting the two charging protocols used. On the back of the results achieved in the body of this dissertation, a new design for the EV simulator was proposed. In this way, space reduction was obtained, and space occupation efficiency was improved with the proposed new design. The testing device thus resulted to be way more compact, enabling to gain in safety and productivity, along with a 25% cost reduction. Furthermore, parallel charging was implemented in the proposed new design since the conducted tests clearly showed the feasibility of parallel charging sessions. The results presented in this work can thus be implemented to build the first prototype of the new EV simulator.

Design of virtual aircraft multipurpose platform

This report elaborates on the master degree thesis developed by the candidate within the company Superjet International. The performed activity focuses on the study and design of VAMP (Virtual Aircraft Multipurpose Platform). VAMP is a new interactive platform, not necessarily limited to the Aeronautical sector, aimed to analyse technical failures, identify risk and recommend the most appropriate corrective actions for maintenance cost reduction, taking into account reliability, availability, maintainability and safety.

Evolution of the structural and fracture design of the ISS payloads due to the new launchers, specifically applied to Biolab IEC-2 projects

The relatively young discipline of astronautics represents one of the scientifically most fascinating and technologically advanced achievements of our time. The human exploration in space does not offer only extraordinary research possibilities but also demands high requirements from man and technology. The space environment provides a lot of attractive experimental tools towards the understanding of fundamental mechanism in natural sciences. It has been shown that especially reduced gravity and elevated radiation, two distinctive factors in space, influence the behavior of biological systems significantly. For this reason one of the key objectives on board of an earth orbiting laboratory is the research in the field of life sciences, covering the broad range from botany, human physiology and crew health up to biotechnology. The Columbus Module is the only European low gravity platform that allows researchers to perform ambitious experiments in a continuous time frame up to several months. Biolab is part of the initial outfitting of the Columbus Laboratory; it is a multi-user facility supporting research in the field of biology, e.g. effect of microgravity and space radiation on cell cultures, micro-organisms, small plants and small invertebrates. The Biolab IEC are projects designed to work in the automatic part of Biolab. In this moment in the TO-53 department of Airbus Defence & Space (formerly Astrium) there are two experiments that are in phase C/D of the development and they are the subject of this thesis: CELLRAD and CYTOSKELETON. They will be launched in soft configuration, that means packed inside a block of foam that has the task to reduce the launch loads on the payload. Until 10 years ago the payloads which were launched in soft configuration were supposed to be structural safe by themselves and a specific structural analysis could be waived on them; with the opening of the launchers market to private companies (that are not under the direct control of the international space agencies), the requirements on the verifications of payloads are changed and they have become much more conservative. In 2012 a new random environment has been introduced due to the new Space-X launch specification that results to be particularly challenging for the soft launched payloads. The last ESA specification requires to perform structural analysis on the payload for combined loads (random vibration, quasi-steady acceleration and pressure). The aim of this thesis is to create FEM models able to reproduce the launch configuration and to verify that all the margins of safety are positive and to show how they change because of the new Space-X random environment. In case the results are negative, improved design solution are implemented. Based on the FEM result a study of the joins has been carried out and, when needed, a crack growth analysis has been performed.

Design of an indirectly fired gas turbine integrated with an organic rankine cycle unit for combined heat and power production

In the last years, the European countries have paid increasing attention to renewable sources and greenhouse emissions. The Council of the European Union and the European Parliament have established ambitious targets for the next years. In this scenario, biomass plays a prominent role since its life cycle produces a zero net carbon dioxide emission. Additionally, biomass can ensure plant operation continuity thanks to its availability and storage ability. Several conventional systems running on biomass are available at the moment. Most of them are performant either in the large-scale or in the small power range. The absence of an efficient system on the small-middle scale inspired this thesis project. The object is an innovative plant based on a wet indirectly fired gas turbine (WIFGT) integrated with an organic Rankine cycle (ORC) unit for combined heat and power production. The WIFGT is a performant system in the small-middle power range; the ORC cycle is capable of giving value to low-temperature heat sources. Their integration is investigated in this thesis with the aim of carrying out a preliminary design of the components. The targeted plant output is around 200 kW in order not to need a wide cultivation area and to avoid biomass shipping. Existing in-house simulation tools are used: They are adapted to this purpose. Firstly the WIFGT + ORC model is built; Zero-dimensional models of heat exchangers, compressor, turbines, furnace, dryer and pump are used. Different fluids are selected but toluene and benzene turn out to be the most suitable. In the indirectly fired gas turbine a pressure ratio around 4 leads to the highest efficiency. From the thermodynamic analysis the system shows an electric efficiency of 38%, outdoing other conventional plants in the same power range. The combined plant is designed to recover thermal energy: Water is used as coolant in the condenser. It is heated from 60°C up to 90°C, ensuring the possibility of space heating. Mono-dimensional models are used to design the heat exchange equipment. Different types of heat exchangers are chosen depending on the working temperature. A finned-plate heat exchanger is selected for the WIFGT heat transfer equipment due to the high temperature, oxidizing and corrosive environment. A once-through boiler with finned tubes is chosen to vaporize the organic fluid in the ORC. A plate heat exchanger is chosen for the condenser and recuperator. A quasi-monodimensional model for single-stage axial turbine is implemented to design both the WIFGT and the ORC turbine. The system simulation after the components design shows an electric efficiency around 34% with a decrease by 10% compared to the zero-dimensional analysis. The work exhibits the system potentiality compared to the existing plants from both technical and economic point of view.

Application of the Equivalent Static Analysis method to the design of a steel frame structure with added viscous dampers

All the structures designed by engineers are vulnerable to natural disasters including floods and earthquakes. The energy released during strong ground motions should be dissipated by structural elements. Before 1990’s, this energy was expected to be dissipated through the beams and columns which at the same time were a part of gravity-load-resisting system. However, the main disadvantage of this idea was that gravity-resisting-frame was not repairable. Hence, during 1990’s, the idea of designing passive energy dissipation systems, including dampers, emerged. At the beginning, main problem was lack of guidelines for passive energy dissipation systems. Although till 2000 many guidelines and procedures where published, yet most of them were based on complicated analysis which was not so convenient for engineers and practitioners. In order to solve this problem recently some alternative design methods are proposed including 1. Lopez Garcia (2001) simple procedure for optimal damper configuration in MDOF structures 2. Christopoulos and Filiatrault (2006) trial and error procedure 3. Silvestri et al. (2010) Five-Step Method. 4. Palermo et al. (2015) Direct Five-Step Method. 5. Palermo et al. (2016) Simplified Equivalent Static Analysis (ESA). In this study, effectiveness and differences between last three alternative methods have been evaluated.

Machine Learning Unsupervised Methods in the Design of an On-board Health Monitoring System for Satellite Applications

The dissertation starts by providing a description of the phenomena related to the increasing importance recently acquired by satellite applications. The spread of such technology comes with implications, such as an increase in maintenance cost, from which derives the interest in developing advanced techniques that favor an augmented autonomy of spacecrafts in health monitoring. Machine learning techniques are widely employed to lay a foundation for effective systems specialized in fault detection by examining telemetry data. Telemetry consists of a considerable amount of information; therefore, the adopted algorithms must be able to handle multivariate data while facing the limitations imposed by on-board hardware features. In the framework of outlier detection, the dissertation addresses the topic of unsupervised machine learning methods. In the unsupervised scenario, lack of prior knowledge of the data behavior is assumed. In the specific, two models are brought to attention, namely Local Outlier Factor and One-Class Support Vector Machines. Their performances are compared in terms of both the achieved prediction accuracy and the equivalent computational cost. Both models are trained and tested upon the same sets of time series data in a variety of settings, finalized at gaining insights on the effect of the increase in dimensionality. The obtained results allow to claim that both models, combined with a proper tuning of their characteristic parameters, successfully comply with the role of outlier detectors in multivariate time series data. Nevertheless, under this specific context, Local Outlier Factor results to be outperforming One-Class SVM, in that it proves to be more stable over a wider range of input parameter values. This property is especially valuable in unsupervised learning since it suggests that the model is keen to adapting to unforeseen patterns.