Lithium-Ion Battery Optimal Charging Using Moth-Flame Optimization Algorithm and Fractional-Order Model

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Abstract
Considering the increasingly serious environmental pollution and energy crisis, new energy electric vehicles have good application prospects in future transportation. The lithium-ion battery is a kind of energy storage device widely used in electric vehicles. An efficient and optimal charging strategy is the premise of its extensive use. In this paper, a fractional model-based multi-stage charging strategy using Moth-flame Optimization (MFO) Algorithm is presented, in which the charging current is divided into several stages. Considering the convenience and safety of the charging process, the charging time, temperature rise, and energy loss are selected as optimization objectives. The MFO algorithm, which has the advantages of simple structure and excellent local search capacity, is employed to optimize the charging performance. Through experiments and simulations, the impacts of the current stage number, cut-off voltage, and weights of each fitness function part on the charging effect are discussed respectively. This paper provides guidance for optimal charging of lithium-ion batteries under different demands in practice.
Funding Information
  • National Natural Science Foundation of China (61803359)
  • National Key Research and Development Program of China (2020YFB1712400)

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