Modeling and simulation of magnet-coil arrays for vibrational energy harvesting in agricultural electric vehicles - Divine Kobbi, Mbanwei; Alombah , Njimboh Henry; Ngwabie, Ngwa Martin (University of Muhammadiyah Malang, 2024)
Electric vehicles have advantages such as reduced maintenance and fuel costs compared to internal combustion engines. However, their limited driving range still hinders their widespread adoption compared to internal combustion engines. Harvesting wasted energies through vibrations in electric vehicles is a good approach to complement the energy of their batteries. Space constraints in electric vehicles require devices with high power output per unit volume. This study aimed to design a novel vibration energy harvesting using the geometrical model for electric vehicles. Different configurations and their performance in maximum flux linkage, electromagnetic coupling coefficient, induced voltage, and generated power were investigated. The modeling, excitement, and analysis were conducted using ANSYS Maxwell software with four configurations under similar conditions. These were the Halbach array with three magnets, one coil, and flat back shield; the Halbach array with three magnets and one coil with a stepped back shield; the double magnet array with two magnets, one coil, and flat back shield; and the fourth one was a double magnet array with two magnets, one coil and stepped back shield. The MATLAB Simulink software was used to obtain further results and power output analysis. The results of the analysis show that the Halbach array with three magnets, one coil, and a stepped-back shield is the best configuration for harvesting energy from vibrations, producing an electromagnetic coupling coefficient of up to 110 Wb/m, a voltage of up to 36 V, and generated power density of 0.13 W/cm. A reasonable increase in output using less volume was obtained compared to the other studies. The energy harvested will be applied in future studies to extend the range of agricultural electric vehicles, reducing farmers’ income spent on fuel and maintenance.