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Single and multi‐objective optimization for the performance enhancement of lead–acid battery cell
Author(s) -
Pourmirzaagha Hamoon,
Esfahanian Vahid,
Sabetghadam Fereidoun,
Torabi Farschad
Publication year - 2016
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.3574
Subject(s) - lead–acid battery , battery (electricity) , particle swarm optimization , energy storage , energy (signal processing) , automotive engineering , computer science , mathematical optimization , process engineering , simulation , engineering , algorithm , mathematics , power (physics) , statistics , physics , quantum mechanics
Summary Electric energy storage systems are used considerably in industries and daily applications. The demand for batteries with high energy content has increased because of their use in hybrid vehicles. Lead–acid batteries have wide applications because of their advantages such as high safety factor and low cost of production. The major shortcoming of lead–acid batteries is low energy content and high dimension and weight. Nowadays, a common method to increase the energy content of lead–acid battery is the experimental method with trial and error, which is time consuming and expensive. In this paper, non‐isothermal one‐dimensional numerical simulation of lead–acid battery with finite volume method is performed. In addition, a cell with higher energy content and lower thickness is designed by using particle swarm optimization algorithm based on developed simulation code. The results of single objective optimization show that an optimal battery that has 27.6% higher energy can be made with the same cell dimension. The results also show that an optimum cell battery can be obtained with a decrease of 24% in thickness while keeping the energy the same. Moreover, a multi‐objective optimization algorithm is utilized to find Pareto optimal solutions while considering the energy content and thickness objectives simultaneously. Copyright © 2016 John Wiley & Sons, Ltd.