LAUSR

There are worldwide tendencies to reduce greenhouse gas emissions toward sustainable communities. The increase in the penetration of electric vehicles (EVs) is an important strategy, which requires the development of regular and fast charging infrastructures. A flywheel fast charging system (FFCS) is proposed to provide reliable fast charging infrastructures for e-buses and EVs using flywheel technology. This paper presents an advanced computational intelligence technique based on an enhanced artificial immune system (EAIS) to improve the performance of the FFCS to support transportation electrification. FFCSs are optimally integrated with utility grid networks, where they offer loading balance and grid protection from any collapse. In addition, the FFCS can achieve a significant reduction in energy costs and maximize energy supply from clean energy resources. The EAIS is an advanced optimization technique that is proposed to tune the optimal dynamic parameters of the FFCS to achieve the improved response. MATLAB/Simulink simulations show results that prove the effectiveness of the proposed system.