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.

BioTuCSoN: biochemical extension of TuCSoN to support self-organising coordination

Starting from pervasive computing paradigm, we want to face the new system's requirements, concerning, mainly, self-organisation, situatedness and adaptivity, through the definition and execution of nature-inspired patterns. They are extracted by the study of dynamics in biological systems and we consider for their implementation the biochemical tuple spaces model. In particular, the aim of the thesis is to design and realize a first biochemical extension of TuCSoN (technology based on tuple spaces model) and, then, to verify its capabilities by means of a proper case study, that deals with local self-organisation and competition of services in an open and highly-dynamic environment.

Hardware/Software Design of Dynamic Real-Time Schedulers for Embedded Multiprocessor Systems

The new generation of multicore processors opens new perspectives for the design of embedded systems. Multiprocessing, however, poses new challenges to the scheduling of real-time applications, in which the ever-increasing computational demands are constantly flanked by the need of meeting critical time constraints. Many research works have contributed to this field introducing new advanced scheduling algorithms. However, despite many of these works have solidly demonstrated their effectiveness, the actual support for multiprocessor real-time scheduling offered by current operating systems is still very limited. This dissertation deals with implementative aspects of real-time schedulers in modern embedded multiprocessor systems. The first contribution is represented by an open-source scheduling framework, which is capable of realizing complex multiprocessor scheduling policies, such as G-EDF, on conventional operating systems exploiting only their native scheduler from user-space. A set of experimental evaluations compare the proposed solution to other research projects that pursue the same goals by means of kernel modifications, highlighting comparable scheduling performances. The principles that underpin the operation of the framework, originally designed for symmetric multiprocessors, have been further extended first to asymmetric ones, which are subjected to major restrictions such as the lack of support for task migrations, and later to re-programmable hardware architectures (FPGAs). In the latter case, this work introduces a scheduling accelerator, which offloads most of the scheduling operations to the hardware and exhibits extremely low scheduling jitter. The realization of a portable scheduling framework presented many interesting software challenges. One of these has been represented by timekeeping. In this regard, a further contribution is represented by a novel data structure, called addressable binary heap (ABH). Such ABH, which is conceptually a pointer-based implementation of a binary heap, shows very interesting average and worst-case performances when addressing the problem of tick-less timekeeping of high-resolution timers.

Development of control-oriented models of Dual Clutch Transmission systems

A control-oriented model of a Dual Clutch Transmission was developed for real-time Hardware In the Loop (HIL) applications, to support model-based development of the DCT controller. The model is an innovative attempt to reproduce the fast dynamics of the actuation system while maintaining a step size large enough for real-time applications. The model comprehends a detailed physical description of hydraulic circuit, clutches, synchronizers and gears, and simplified vehicle and internal combustion engine sub-models. As the oil circulating in the system has a large bulk modulus, the pressure dynamics are very fast, possibly causing instability in a real-time simulation; the same challenge involves the servo valves dynamics, due to the very small masses of the moving elements. Therefore, the hydraulic circuit model has been modified and simplified without losing physical validity, in order to adapt it to the real-time simulation requirements. The results of offline simulations have been compared to on-board measurements to verify the validity of the developed model, that was then implemented in a HIL system and connected to the TCU (Transmission Control Unit). Several tests have been performed: electrical failure tests on sensors and actuators, hydraulic and mechanical failure tests on hydraulic valves, clutches and synchronizers, and application tests comprehending all the main features of the control performed by the TCU. Being based on physical laws, in every condition the model simulates a plausible reaction of the system. The first intensive use of the HIL application led to the validation of the new safety strategies implemented inside the TCU software. A test automation procedure has been developed to permit the execution of a pattern of tests without the interaction of the user; fully repeatable tests can be performed for non-regression verification, allowing the testing of new software releases in fully automatic mode.

A multi-objective genetic algorithm optimisation using variable speed pumps in water distribution systems

Due to its practical importance and inherent complexity, the optimisation of distribution networks for supplying drinking water has been the subject of extensive study for the past 30 years. The optimization is governed by sizing the pipes in the water distribution network (WDN) and / or optimises specific parts of the network such as pumps, tanks etc. or try to analyse and optimise the reliability of a WDN. In this thesis, the author has analysed two different WDNs (Anytown City and Cabrera city networks), trying to solve and optimise a multi-objective optimisation problem (MOOP). The main two objectives in both cases were the minimisation of Energy Cost (€) or Energy consumption (kWh), along with the total Number of pump switches (TNps) during a day. For this purpose, a decision support system generator for Multi-objective optimisation used. Its name is GANetXL and has been developed by the Center of Water System in the University of Exeter. GANetXL, works by calling the EPANET hydraulic solver, each time a hydraulic analysis has been fulfilled. The main algorithm used, was a second-generation algorithm for multi-objective optimisation called NSGA_II that gave us the Pareto fronts of each configuration. The first experiment that has been carried out was the network of Anytown city. It is a big network with a pump station of four fixed speed parallel pumps that are boosting the water dynamics. The main intervention was to change these pumps to new Variable speed driven pumps (VSDPs), by installing inverters capable to diverse their velocity during the day. Hence, it’s been achieved great Energy and cost savings along with minimisation in the number of pump switches. The results of the research are thoroughly illustrated in chapter 7, with comments and a variety of graphs and different configurations. The second experiment was about the network of Cabrera city. The smaller WDN had a unique FS pump in the system. The problem was the same as far as the optimisation process was concerned, thus, the minimisation of the energy consumption and in parallel the minimisation of TNps. The same optimisation tool has been used (GANetXL).The main scope was to carry out several and different experiments regarding a vast variety of configurations, using different pump (but this time keeping the FS mode), different tank levels, different pipe diameters and different emitters coefficient. All these different modes came up with a large number of results that were compared in the chapter 8. Concluding, it should be said that the optimisation of WDNs is a very interested field that has a vast space of options to deal with. This includes a large number of algorithms to choose from, different techniques and configurations to be made and different support system generators. The researcher has to be ready to “roam” between these choices, till a satisfactory result will convince him/her that has reached a good optimisation point.

Operating System Contribution to Composable Timing Behaviour in High-Integrity Real-Time Systems

The development of High-Integrity Real-Time Systems has a high footprint in terms of human, material and schedule costs. Factoring functional, reusable logic in the application favors incremental development and contains costs. Yet, achieving incrementality in the timing behavior is a much harder problem. Complex features at all levels of the execution stack, aimed to boost average-case performance, exhibit timing behavior highly dependent on execution history, which wrecks time composability and incrementaility with it. Our goal here is to restitute time composability to the execution stack, working bottom up across it. We first characterize time composability without making assumptions on the system architecture or the software deployment to it. Later, we focus on the role played by the real-time operating system in our pursuit. Initially we consider single-core processors and, becoming less permissive on the admissible hardware features, we devise solutions that restore a convincing degree of time composability. To show what can be done for real, we developed TiCOS, an ARINC-compliant kernel, and re-designed ORK+, a kernel for Ada Ravenscar runtimes. In that work, we added support for limited-preemption to ORK+, an absolute premiere in the landscape of real-word kernels. Our implementation allows resource sharing to co-exist with limited-preemptive scheduling, which extends state of the art. We then turn our attention to multicore architectures, first considering partitioned systems, for which we achieve results close to those obtained for single-core processors. Subsequently, we shy away from the over-provision of those systems and consider less restrictive uses of homogeneous multiprocessors, where the scheduling algorithm is key to high schedulable utilization. To that end we single out RUN, a promising baseline, and extend it to SPRINT, which supports sporadic task sets, hence matches real-world industrial needs better. To corroborate our results we present findings from real-world case studies from avionic industry.

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.

Classification algorithms for Intelligent Transport Systems

Intelligent Transport Systems (ITS) consists in the application of ICT to transport to offer new and improved services to the mobility of people and freights. While using ITS, travellers produce large quantities of data that can be collected and analysed to study their behaviour and to provide information to decision makers and planners. The thesis proposes innovative deployments of classification algorithms for Intelligent Transport System with the aim to support the decisions on traffic rerouting, bus transport demand and behaviour of two wheelers vehicles. The first part of this work provides an overview and a classification of a selection of clustering algorithms that can be implemented for the analysis of ITS data. The first contribution of this thesis is an innovative use of the agglomerative hierarchical clustering algorithm to classify similar travels in terms of their origin and destination, together with the proposal for a methodology to analyse drivers’ route choice behaviour using GPS coordinates and optimal alternatives. The clusters of repetitive travels made by a sample of drivers are then analysed to compare observed route choices to the modelled alternatives. The results of the analysis show that drivers select routes that are more reliable but that are more expensive in terms of travel time. Successively, different types of users of a service that provides information on the real time arrivals of bus at stop are classified using Support Vector Machines. The results shows that the results of the classification of different types of bus transport users can be used to update or complement the census on bus transport flows. Finally, the problem of the classification of accidents made by two wheelers vehicles is presented together with possible future application of clustering methodologies aimed at identifying and classifying the different types of accidents.

Connectivity management and dynamic context grouping in mobile heterogenous systems

In the last 10 years the number of mobile devices has grown rapidly. Each person usually brings at least two personal devices and researchers says that in a near future this number could raise up to ten devices per person. Moreover, all the devices are becoming more integrated to our life than in the past, therefore the amount of data exchanged increases accordingly to the improvement of people's lifestyle. This is what researchers call Internet of Things. Thus, in the future there will be more than 60 billions of nodes and the current infrastructure is not ready to keep track of all the exchanges of data between them. Therefore, infrastructure improvements have been proposed in the last years, like MobileIP and HIP in order to facilitate the exchange of packets in mobility, however none of them have been optimized for the purpose. In the last years, researchers from Mid Sweden University created The MediaSense Framework. Initially, this framework was based on the Chord protocol in order to route packets in a big network, but the most important change has been the introduction of PGrids in order to create the Overlay and the persistence. Thanks to this technology, a lookup in the trie takes up to 0.5*log(N), where N is the total number of nodes in the network. This result could be improved by further optimizations on the management of the nodes, for example by the dynamic creation of groups of nodes. Moreover, since the nodes move, an underlaying support for connectivity management is needed. SCTP has been selected as one of the most promising upcoming standards for simultaneous multiple connection's management.

Modelling and simulating in systems biology: an approach based on multi-agent systems

Systems Biology is an innovative way of doing biology recently raised in bio-informatics contexts, characterised by the study of biological systems as complex systems with a strong focus on the system level and on the interaction dimension. In other words, the objective is to understand biological systems as a whole, putting on the foreground not only the study of the individual parts as standalone parts, but also of their interaction and of the global properties that emerge at the system level by means of the interaction among the parts. This thesis focuses on the adoption of multi-agent systems (MAS) as a suitable paradigm for Systems Biology, for developing models and simulation of complex biological systems. Multi-agent system have been recently introduced in informatics context as a suitabe paradigm for modelling and engineering complex systems. Roughly speaking, a MAS can be conceived as a set of autonomous and interacting entities, called agents, situated in some kind of nvironment, where they fruitfully interact and coordinate so as to obtain a coherent global system behaviour. The claim of this work is that the general properties of MAS make them an effective approach for modelling and building simulations of complex biological systems, following the methodological principles identified by Systems Biology. In particular, the thesis focuses on cell populations as biological systems. In order to support the claim, the thesis introduces and describes (i) a MAS-based model conceived for modelling the dynamics of systems of cells interacting inside cell environment called niches. (ii) a computational tool, developed for implementing the models and executing the simulations. The tool is meant to work as a kind of virtual laboratory, on top of which kinds of virtual experiments can be performed, characterised by the definition and execution of specific models implemented as MASs, so as to support the validation, falsification and improvement of the models through the observation and analysis of the simulations. A hematopoietic stem cell system is taken as reference case study for formulating a specific model and executing virtual experiments.

Rural water system sustainability : a case study of community-managed water systems in Saramaka communities

Worldwide, rural populations are far less likely to have access to clean drinking water than are urban ones. In many developing countries, the current approach to rural water supply uses a model of demand-driven, community-managed water systems. In Suriname, South America rural populations have limited access to improved water supplies; community-managed water supply systems have been installed in several rural communities by nongovernmental organizations as part of the solution. To date, there has been no review of the performance of these water supply systems. This report presents the results of an investigation of three rural water supply systems constructed in Saramaka villages in the interior of Suriname. The investigation used a combination of qualitative and quantitative methods, coupled with ethnographic information, to construct a comprehensive overview of these water systems. This overview includes the water use of the communities, the current status of the water supply systems, histories and sustainability of the water supply projects, technical reviews, and community perceptions. From this overview, factors important to the sustainability of these water systems were identified. Community water supply systems are engineered solutions that operate through social cooperation. The results from this investigation show that technical adequacy is the first and most critical factor for long-term sustainability of a water system. It also shows that technical adequacy is dependent on the appropriateness of the engineering design for the social, cultural, and natural setting in which it takes place. The complex relationships between technical adequacy, community support, and the involvement of women play important roles in the success of water supply projects. Addressing these factors during the project process and taking advantage of alternative water resources may increase the supply of improved drinking water to rural communities.

Community managed rural water supply systems in the Dominican Republic : assessment of sustainability of systems built by the National Institute of Potable Water and Peace Corps, Dominican Republic

In the Dominican Republic economic growth in the past twenty years has not yielded sufficient improvement in access to drinking water services, especially in rural areas where 1.5 million people do not have access to an improved water source (WHO, 2006). Worldwide, strategic development planning in the rural water sector has focused on participatory processes and the use of demand filters to ensure that service levels match community commitment to post-project operation and maintenance. However studies have concluded that an alarmingly high percentage of drinking water systems (20-50%) do not provide service at the design levels and/or fail altogether (up to 90%): BNWP (2009), Annis (2006), and Reents (2003). World Bank, USAID, NGOs, and private consultants have invested significant resources in an effort to determine what components make up an “enabling environment” for sustainable community management of rural water systems (RWS). Research has identified an array of critical factors, internal and external to the community, which affect long term sustainability of water services. Different frameworks have been proposed in order to better understand the linkages between individual factors and sustainability of service. This research proposes a Sustainability Analysis Tool to evaluate the sustainability of RWS, adapted from previous relevant work in the field to reflect the realities in the Dominican Republic. It can be used as a diagnostic tool for government entities and development organizations to characterize the needs of specific communities and identify weaknesses in existing training regimes or support mechanisms. The framework utilizes eight indicators in three categories (Organization/Management, Financial Administration, and Technical Service). Nineteen independent variables are measured resulting in a score of sustainability likely (SL), possible (SP), or unlikely (SU) for each of the eight indicators. Thresholds are based upon benchmarks from the DR and around the world, primary data collected during the research, and the author’s 32 months of field experience. A final sustainability score is calculated using weighting factors for each indicator, derived from Lockwood (2003). The framework was tested using a statistically representative geographically stratified random sample of 61 water systems built in the DR by initiatives of the National Institute of Potable Water (INAPA) and Peace Corps. The results concluded that 23% of sample systems are likely to be sustainable in the long term, 59% are possibly sustainable, and for 18% it is unlikely that the community will be able to overcome any significant challenge. Communities that were scored as unlikely sustainable perform poorly in participation, financial durability, and governance while the highest scores were for system function and repair service. The Sustainability Analysis Tool results are verified by INAPA and PC reports, evaluations, and database information, as well as, field observations and primary data collected during the surveys. Future research will analyze the nature and magnitude of relationships between key factors and the sustainability score defined by the tool. Factors include: gender participation, legal status of water committees, plumber/operator remuneration, demand responsiveness, post construction support methodologies, and project design criteria.

Estimating greenhouse gas emissions of highway construction and rehabilitation to support pavement life cycle assessment

Highway infrastructure plays a significant role in society. The building and upkeep of America’s highways provide society the necessary means of transportation for goods and services needed to develop as a nation. However, as a result of economic and social development, vast amounts of greenhouse gas emissions (GHG) are emitted into the atmosphere contributing to global climate change. In recognizing this, future policies may mandate the monitoring of GHG emissions from public agencies and private industries in order to reduce the effects of global climate change. To effectively reduce these emissions, there must be methods that agencies can use to quantify the GHG emissions associated with constructing and maintaining the nation’s highway infrastructure. Current methods for assessing the impacts of highway infrastructure include methodologies that look at the economic impacts (costs) of constructing and maintaining highway infrastructure over its life cycle. This is known as Life Cycle Cost Analysis (LCCA). With the recognition of global climate change, transportation agencies and contractors are also investigating the environmental impacts that are associated with highway infrastructure construction and rehabilitation. A common tool in doing so is the use of Life Cycle Assessment (LCA). Traditionally, LCA is used to assess the environmental impacts of products or processes. LCA is an emerging concept in highway infrastructure assessment and is now being implemented and applied to transportation systems. This research focuses on life cycle GHG emissions associated with the construction and rehabilitation of highway infrastructure using a LCA approach. Life cycle phases of the highway section include; the material acquisition and extraction, construction and rehabilitation, and service phases. Departing from traditional approaches that tend to use LCA as a way to compare alternative pavement materials or designs based on estimated inventories, this research proposes a shift to a context sensitive process-based approach that uses actual observed construction and performance data to calculate greenhouse gas emissions associated with highway construction and rehabilitation. The goal is to support strategies that reduce long-term environmental impacts. Ultimately, this thesis outlines techniques that can be used to assess GHG emissions associated with construction and rehabilitation operations to support the overall pavement LCA.

EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.