Premium
Energy storage and control optimization for an electric vehicle
Author(s) -
Javorski Eckert Jony,
Corrêa de Alkmin e Silva Ludmila,
Mazzariol Santiciolli Fabio,
Santos Costa Eduardo,
Corrêa Fernanda Cristina,
Giuseppe Dedini Franco
Publication year - 2018
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.4089
Subject(s) - electric vehicle , energy management , pareto principle , genetic algorithm , range (aeronautics) , battery (electricity) , energy storage , automotive engineering , engineering , energy (signal processing) , control (management) , power (physics) , energy management system , fuzzy logic , computer science , mathematical optimization , mathematics , operations management , physics , quantum mechanics , artificial intelligence , statistics , aerospace engineering
Summary Two big issues involving electric vehicles are energy supply and power management control. To deal with the energy supply problem, this paper proposes the application of a hybrid energy source system, composed of battery pack and ultracapacitor bank. The power management control between the energy supplies was defined by a fuzzy logic with inference rules optimized through genetic algorithm. The genetic algorithm optimizes lower and upper limits of membership functions aiming to reduce the hybrid energy source system total mass while maximizing the electric vehicle drive range and performance. Through the Pareto frontier, we found the best trade‐off solution.