This paper deals with a power sensitivity improvement of an electromagnetic vibration energy harvester which generates electrical energy from ambient vibrations. The harvester provides an autonomous source of energy for wireless applications, with an expected power consumption of several mW, placed in environment excited by ambient mechanical vibrations. An appropriately tuned up design of the harvester with adequate sensitivity provides sufficient generating of electrical energy for some wireless applications and maximal harvested power depends on a harvester mass, frequency and level of the vibration and sensitivity of the energy harvester. The design of our harvester is based on electromagnetic converter and it contains a unique spring-less resonance mechanism where stiffness is provided by repelled magnetic forces. The greater sensitivity of the harvester provides more generated power or decrease of the harvester size and weight.

This paper deals with optimization studies based on artificial intelligence methods. These modern optimization methods can be very useful for design improving of an electromagnetic vibration energy harvester. The vibration energy harvester is a complex mechatronic device which harvests electrical energy from ambient mechanical vibrations. The harvester design consists of a precise mechanical resonator, electromagnetic converter and electronics. The optimization study of such complex mechatronic device is complicated however artificial intelligence methods can be used for set up of optimal harvester parameters. Used optimization strategies are applied to optimize the design of the electro-magnetic vibration energy harvester according to multi-objective fitness functions. Optimization results of the harvester are summarized in this paper. Presented optimization algorithms can be used for a design of new energy harvesting systems or for improving on existing energy harvesting systems.

No abstract

No abstract

No abstract