Recently the technology development and increasing amounts of investment in renewables has led to a growing interest towards design and optimization of green energy systems. In this context, advanced Computational Intelligence (CI) techniques can be applied by engineers to several technical problems in order to find out the best structure and to improve efficiency in energy recovery. This research promises to give new impulse to using innovative unconventional renewable sources and to develop the so-called Energy Harvesting Devices (EHDs). In this paper, the optimization of a Tubular Permanent Magnet-Linear Generator for energy harvesting from vehicles to grid is presented. 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.
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