The recently increase of the EV/PHEV market is in part due to the technological progress of battery systems. The energy storage and charging are the critical aspects of an electric vehicle; Li-Ion batteries allow an increase in storage performance and efficiencies despite the needs of a high number of cells. The single Li-Ion cell is constituted by metals, graphite, various salts and electrolytes which result difficult to dispose of or recycle. Therefore the expected environmental sustainability of any EV is limited by the final impact of battery production and disposal. The proposed research studies the Second Life applications suitable for the Li-Ion battery cells used for electric powertrains in order to promote a Sustainable Transportation and avoid the environmental impact that disposal of these batteries would have. A Life Cycle Assessment (LCA) analysis has been adopted to estimate the gain in terms of environmental impact provided by reusing disposed Li-Ion cells for a Second Life application. An automotive battery pack with LiFePO4 cells has been chosen as a test case, then the life-cycle due to vehicle loads has been predicted by accelerated tests and the residual cell capacity has been experimentally evaluated. A possible Second Life scenario has been studied for the automotive Li-Ion batteries: reusing the disposed cell in a smart grid system after vehicle use to provide the grid energy stabilization and storage. This strategy has been evaluated with an LCA tool taking into account materials (anode, cathode, separator, et.), as well as flows and processes (production, assembly, disassembly) both for production and reuse phases. The research results show a positive effect of the Second Life solution on the environmental impact of the Li-Ion cells; moreover, the collected data will be useful for the Second Life strategies and scheduling during the early design phase.

Steel constructions are widely used in several applications such as structures for buildings, stores, factories, and power plants. The scope of the research is to study a methodology to reduce the weight and the cost related to big frame steel structures during the early design phase, which is the phase where most of the project layout is defined. The main aim of this paper is the development of a platform-tool to support the automatic optimization of a steel structure using virtual prototyping tools and genetic algorithms. The focus is on the design of heavy steel structures for oil & gas power plants. This work describes in detail the design methodology and estimates the weight saving related to the re-design process of a test case structure. The design cases considered in the paper are those relevant to the operating