A lifetime optimization method of new energy storage module based on new artificial fish swarm algorithm

Pengfei Zhi,Haiyang Qiu,Weiran Wang,Yongshuang Qi,Ye Yang,Wanlu Zhu

doi:10.1177/16878140211050843

Pengfei Zhi, Haiyang Qiu + Show 4 more

Open Access

https://doi.org/10.1177/16878140211050843

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Abstract

The demand for new energy will continue to expand as the environment changes and fossil energy decreases. However, the instability of new energy has slowed down the development of new energy. The joint use of new energy and energy storage modules effectively solves the shortcomings of new energy. The article proposed a lifetime optimization method of new energy storage module based on new artificial fish swarm algorithm. Firstly the life model based on the battery capacity [Formula: see text], charging current [Formula: see text], and discharge current [Formula: see text] is built. Secondly, the deep learning method is used to improve the step length and speed change of artificial fish-school algorithm. Finally, the simulation platform detects the optimized parameters [Formula: see text]. The simulation results show that optimized parameters can help extend the life of the energy storage module.

Highlights

The energy storage module can solve the problem of instability of the power supply system caused by new energy
The single battery storage device will face the question of frequent changes function
The article improves the step size of the fish school algorithm based on deep learning

Summary

Introduction

Domestic and foreign scholars are beginning to research the development of new energy technologies.[1,2,3] The energy storage module can solve the problem of instability of the power supply system caused by new energy. The double battery storage module solves the disadvantages of frequent switching It has a problem of transient voltage during the switching. The control strategy of the three-lithium battery energy storage module can ensure stable output energy, and the optimization performance of the new fish school algorithm is better than the original fish school algorithm and the firefly algorithm. The three-lithium battery energy storage module mainly includes three lithium batteries (Li-ion[1], Li-ion[2], and Li-ion3), monitor device, and control device. The power distribution of Li-ion[1] and Li-ion[2] (Li-ion3) is performed by the controller in the tri-lithium battery energy storage module. The mathematical formula of Li-ion[2] (Li-ion3) allocated power is:

C À Chigh Cmax À Chigh 0

Findings

Conclusions