A path planning strategy with ant colony algorithm for series connected batteries

Yang Chen; Teng Shen; Shiyan Yang; Xiaofang Liu; Ru Yang; Lefeng Cheng

doi:10.3390/electronics9111816

A path planning strategy with ant colony algorithm for series connected batteries

Yang Chen
, Teng Shen^*
, Shiyan Yang
, Xiaofang Liu^*
, Ru Yang
, Lefeng Cheng^*

^*Corresponding author for this work

Guangzhou University
School of Electrical Engineering and Automation, Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

This article presents a path planning strategy with ant colony algorithm for series connected batteries. The motive of this paper is the increasing need for efficient and fast equalization for Lithium-ion batteries. There are many great papers on the design of the equalization circuits. However, they lack the part of path planning strategy for the balancing circuits. To solve this issue, we adopt the graph model to represent the balancing paths among different battery cells and then construct two optimal models based on the best efficiency and speed, respectively. Finally, ant colony algorithm is used to solve these two models. This makes it possible to achieve different goals according to the practical operating conditions. We validate the function of the proposed path planning strategy through an example of 13 series connected battery balancing system.

Original language	English
Article number	1816
Pages (from-to)	1-13
Number of pages	13
Journal	Electronics (Switzerland)
Volume	9
Issue number	11
DOIs	https://doi.org/10.3390/electronics9111816
State	Published - Nov 2020
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Ant colony algorithm
Graph model
Path planning
Series connected batteries
Two-layer balancing structure

Access to Document

10.3390/electronics9111816

Cite this

@article{e54597d9d58142658527ba8f6276d033,

title = "A path planning strategy with ant colony algorithm for series connected batteries",

abstract = "This article presents a path planning strategy with ant colony algorithm for series connected batteries. The motive of this paper is the increasing need for efficient and fast equalization for Lithium-ion batteries. There are many great papers on the design of the equalization circuits. However, they lack the part of path planning strategy for the balancing circuits. To solve this issue, we adopt the graph model to represent the balancing paths among different battery cells and then construct two optimal models based on the best efficiency and speed, respectively. Finally, ant colony algorithm is used to solve these two models. This makes it possible to achieve different goals according to the practical operating conditions. We validate the function of the proposed path planning strategy through an example of 13 series connected battery balancing system.",

keywords = "Ant colony algorithm, Graph model, Path planning, Series connected batteries, Two-layer balancing structure",

author = "Yang Chen and Teng Shen and Shiyan Yang and Xiaofang Liu and Ru Yang and Lefeng Cheng",

note = "Publisher Copyright: {\textcopyright} 2020 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2020",

month = nov,

doi = "10.3390/electronics9111816",

language = "英语",

volume = "9",

pages = "1--13",

journal = "Electronics (Switzerland)",

issn = "2079-9292",

publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",

number = "11",

}

TY - JOUR

T1 - A path planning strategy with ant colony algorithm for series connected batteries

AU - Chen, Yang

AU - Shen, Teng

AU - Yang, Shiyan

AU - Liu, Xiaofang

AU - Yang, Ru

AU - Cheng, Lefeng

PY - 2020/11

Y1 - 2020/11

N2 - This article presents a path planning strategy with ant colony algorithm for series connected batteries. The motive of this paper is the increasing need for efficient and fast equalization for Lithium-ion batteries. There are many great papers on the design of the equalization circuits. However, they lack the part of path planning strategy for the balancing circuits. To solve this issue, we adopt the graph model to represent the balancing paths among different battery cells and then construct two optimal models based on the best efficiency and speed, respectively. Finally, ant colony algorithm is used to solve these two models. This makes it possible to achieve different goals according to the practical operating conditions. We validate the function of the proposed path planning strategy through an example of 13 series connected battery balancing system.

AB - This article presents a path planning strategy with ant colony algorithm for series connected batteries. The motive of this paper is the increasing need for efficient and fast equalization for Lithium-ion batteries. There are many great papers on the design of the equalization circuits. However, they lack the part of path planning strategy for the balancing circuits. To solve this issue, we adopt the graph model to represent the balancing paths among different battery cells and then construct two optimal models based on the best efficiency and speed, respectively. Finally, ant colony algorithm is used to solve these two models. This makes it possible to achieve different goals according to the practical operating conditions. We validate the function of the proposed path planning strategy through an example of 13 series connected battery balancing system.

KW - Ant colony algorithm

KW - Graph model

KW - Path planning

KW - Series connected batteries

KW - Two-layer balancing structure

UR - https://www.scopus.com/pages/publications/85094896780

U2 - 10.3390/electronics9111816

DO - 10.3390/electronics9111816

M3 - 文章

AN - SCOPUS:85094896780

SN - 2079-9292

VL - 9

SP - 1

EP - 13

JO - Electronics (Switzerland)

JF - Electronics (Switzerland)

IS - 11

M1 - 1816

ER -

A path planning strategy with ant colony algorithm for series connected batteries

Abstract

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this