Optimized linear generator for vehicle energy harvesting by social network optimization algorithm

The optimization of electrical machines can be managed using advanced computational intelligence algorithms. These algorithms can speed up the design phase and can improve the performances, being able to find out the optimal design also in problems involving a large number of physical and geometric parameters. In this paper, a new population based metaheuristic algorithms, named Social Network Optimization (SNO), has been used to find the optimal design of a tubular permanent magnet linear generator (TPMLG), in the context of a vehicular energy harvesting system.