Comparative Analysis of Alternative Hybrid Systems for Automotive Applications

The main objective of this work was to investigate the impact of different hybridization concepts and levels of hybridization on fuel economy of a standard road vehicle where both conventional and non-conventional hybrid architectures are treated exactly in the same way from the point of view of overall energy flow optimization. Hybrid component models were developed and presented in detail as well as the simulations results mainly for NEDC cycle. The analysis was performed on four different parallel hybrid powertrain concepts: Hybrid Electric Vehicle (HEV), High Speed Flywheel Hybrid Vehicle (HSF-HV), Hydraulic Hybrid Vehicle (HHV) and Pneumatic Hybrid Vehicle (PHV). In order to perform equitable analysis of different hybrid systems, comparison was performed also on the basis of the same usable system energy storage capacity (i.e. 625kJ for HEV, HSF and the HHV) but in the case of pneumatic hybrid systems maximal storage capacity was limited by the size of the systems in order to comply with the packaging requirements of the vehicle. The simulations were performed within the IAV Gmbh - VeLoDyn software simulator based on Matlab / Simulink software package. Advanced cycle independent control strategy (ECMS) was implemented into the hybrid supervisory control unit in order to solve power management problem for all hybrid powertrain solutions. In order to maintain State of Charge within desired boundaries during different cycles and to facilitate easy implementation and recalibration of the control strategy for very different hybrid systems, Charge Sustaining Algorithm was added into the ECMS framework. Also, a Variable Shift Pattern VSP-ECMS algorithm was proposed as an extension of ECMS capabilities so as to include gear selection into the determination of minimal (energy) cost function of the hybrid system. Further, cycle-based energetic analysis was performed in all the simulated cases, and the results have been reported in the corresponding chapters.

Optimal Supervisory Control of Hybrid Vehicles

Hybrid vehicles (HV), comprising a conventional ICE-based powertrain and a secondary energy source, to be converted into mechanical power as well, represent a well-established alternative to substantially reduce both fuel consumption and tailpipe emissions of passenger cars. Several HV architectures are either being studied or already available on market, e.g. Mechanical, Electric, Hydraulic and Pneumatic Hybrid Vehicles. Among the others, Electric (HEV) and Mechanical (HSF-HV) parallel Hybrid configurations are examined throughout this Thesis. To fully exploit the HVs potential, an optimal choice of the hybrid components to be installed must be properly designed, while an effective Supervisory Control must be adopted to coordinate the way the different power sources are managed and how they interact. Real-time controllers can be derived starting from the obtained optimal benchmark results. However, the application of these powerful instruments require a simplified and yet reliable and accurate model of the hybrid vehicle system. This can be a complex task, especially when the complexity of the system grows, i.e. a HSF-HV system assessed in this Thesis. The first task of the following dissertation is to establish the optimal modeling approach for an innovative and promising mechanical hybrid vehicle architecture. It will be shown how the chosen modeling paradigm can affect the goodness and the amount of computational effort of the solution, using an optimization technique based on Dynamic Programming. The second goal concerns the control of pollutant emissions in a parallel Diesel-HEV. The emissions level obtained under real world driving conditions is substantially higher than the usual result obtained in a homologation cycle. For this reason, an on-line control strategy capable of guaranteeing the respect of the desired emissions level, while minimizing fuel consumption and avoiding excessive battery depletion is the target of the corresponding section of the Thesis.

Development of methodologies supporting the sustainable and safe integration of offshore conventional and renewable energy production

Against a backdrop of rapidly increasing worldwide population and growing energy demand, the development of renewable energy technologies has become of primary importance in the effort to reduce greenhouse gas emissions. However, it is often technically and economically infeasible to transport discontinuous renewable electricity for long distances to the shore. Another shortcoming of non-programmable renewable power is its integration into the onshore grid without affecting the dispatching process. On the other hand, the offshore oil & gas industry is striving to reduce overall carbon footprint from onsite power generators and limiting large expenses associated to carrying electricity from remote offshore facilities. Furthermore, the increased complexity and expansion towards challenging areas of offshore hydrocarbons operations call for higher attention to safety and environmental protection issues from major accident hazards. Innovative hybrid energy systems, as Power-to-Gas (P2G), Power-to-Liquid (P2L) and Gas-to-Power (G2P) options, implemented at offshore locations, would offer the opportunity to overcome challenges of both renewable and oil & gas sectors. This study aims at the development of systematic methodologies based on proper sustainability and safety performance indicators supporting the choice of P2G, P2L and G2P hybrid energy options for offshore green projects in early design phases. An in-depth analysis of the different offshore hybrid strategies was performed. The literature reviews on existing methods proposing metrics to assess sustainability of hybrid energy systems, inherent safety of process routes in conceptual design stage and environmental protection of installations from oil and chemical accidental spills were carried out. To fill the gaps, a suite of specific decision-making methodologies was developed, based on representative multi-criteria indicators addressing technical, economic, environmental and societal aspects of alternative options. A set of five case-studies was defined, covering different offshore scenarios of concern, to provide an assessment of the effectiveness and value of the developed tools.