Novel Speed-Bump Design and Optimization for Energy Harvesting From Traffic

In recent years, the increase in computational capability and development of innovative multiphysic techniques has determined a growing interest toward modeling and optimization in engineering system design for green energy applications. In this field, advanced soft computing techniques can be applied by engineers to several problems and to be used in an optimization process to find out the best design and, thus, to improve the system performance. These techniques also promise to give new impulse to research on renewable systems and, particularly in the last five years, on the so-called energy-harvesting devices (EHDs). This paper presents the optimization of a tubular permanent-magnet linear generator used for applications of energy harvesting from traffic. The optimization process is developed by means of hybrid evolutionary algorithms to reach the best overall system efficiency and the impact on the environment and transportation systems. Finally, an experimental validation of the designed EHD prototype is presented.