The overconsumption of fossil fuels has drastically increased the emissions of toxic gases causing harm to the environment. Batteries are one of the most important components of Electric Vehicles. When dealing with bigger capacities and high power requirements, high power supplying battery packs are required, which consist of several batteries. These high capacity battery packs are prone to reach high temperatures during charging and discharging thus, giving rise to a lot of complications. Hence, the use of a battery management system is essential. It is responsible to optimize the battery pack which results in better and safer working of the battery pack. The main objective of this paper is to simulate a MATLAB/Simulink model of a Battery Management System (BMS) and analyze the different types of estimation methods of the main parameters of a battery management system. It also provides an idea on the most efficient and cost-friendly methods to implement in a BMS. The main parameters include the balancing of the battery pack, state of charge (SoC) estimation methods, state of health (SoH) estimation, charging and discharging control and temperature monitoring, which help improve the performance of the battery.

1.
Du
,
J.
and
Ouyang
,
M.
2013
, November. “
Review of electric vehicle technologies progress and development prospect in china
” in
Electric Vehicle Symposium and Exhibition (EVS27)
,
2013
World (pp.
1
8
)
2.
L.
Buccolini
,
A.
Ricci
,
C.
Scavongelli
,
G.
DeMaso-Gentile
,
S.
Orcioni
and
M.
Conti
, "
Battery Management System (BMS) simulation environment for electric vehicles
,"
2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC
),
2016
, pp.
1
6
, doi: .
3.
D.
Xu
,
L.
Wang
and
J.
Yang
, "
Research on Li-ion Battery Management System
,"
2010 International Conference on Electrical and Control Engineering
,
2010
, pp.
4106
4109
, doi: .
4.
Yang
Wenrong
,
Li
Lulu
, and
Zhan
Junyi
,
“Design for Power Lithium Battery Management System of Electric Vehicle
”,
2013 6th International IEEE Conference on Information Management, Innovation Management and Industrial Engineering
.
5.
T. D. Curi
Busarello
and
M. G.
Simões
, "
A Tutorial on Implementing Kalman Filters with Commonly Used Blocks
,"
IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
,
2019
, pp.
60
67
, doi: .
6.
P.
Singh
,
C.
Chen
,
C. M.
Tan
, and
S.-C.
Huang
, “
Semi-Empirical Capacity Fading Model for SoH Estimation of Li-Ion Batteries
,”
Applied Sciences
, vol.
9
, no.
15
, p.
3012
, Jul.
2019
.
7.
O.
Erdinc
,
B.
Vural
and
M.
Uzunoglu
, "
A dynamic lithium-ion battery model considering the effects of temperature and capacity fading
,"
2009 International Conference on Clean Electrical Power
,
2009
, pp.
383
386
, doi: .
8.
V.
Vaideeswaran
,
S.
Bhuvanesh
and
M.
Devasena
, "
Battery Management Systems for Electric Vehicles using Lithium Ion Batteries
,"
2019 Innovations in Power and Advanced Computing Technologies (i-PACT
),
2019
, pp.
1
9
, doi: .
9.
J.
Qiang
,
L.
Yang
,
G.
Ao
and
H.
Zhong
, "
Battery Management System for Electric Vehicle Application
,"
2006 IEEE International Conference on Vehicular Electronics and Safety
,
2006
, pp.
134
138
, doi: .
10.
L. W.
Yao
,
J. A.
Aziz
,
P. Y.
Kong
and
N. R. N.
Idris
, "
Modeling of lithium-ion battery using MATLAB/simulink
,"
IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society
,
Vienna
,
2013
, pp.
1729
1734
, doi: .
11.
P.
Dost
and
C.
Sourkounis
, "
Battery management system realisation for electric vehicles
,"
22nd Mediterranean Conference on Control and Automation, Palermo
,
2014
, pp.
704
709
.
12.
K.
Rahul
,
J.
Ramprabhakar
and
S.
Shankar
, "
Comparative study on modeling and estimation of State of Charge in battery
,"
2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon
),
2017
, pp.
1610
1615
, doi: .
13.
P. R.
Shabarish
,
D. V. S. Sai
Aditya
,
V. V. S. S. Phani
Pavan
and
P. V.
Manitha
, "
SOC Estimation of battery in Hybrid Vehicle Using Adaptive Neuro-Fuzzy Technique
,"
2020
International Conference on Smart Electronics and Communication (ICOSEC
),
2020
, pp.
445
450
, doi: .
14.
T.
Duraisamy
and
Dr. K.
Deepa
, “
Active cell balancing for electric vehicle battery management system
”,
International Journal of Power Electronics and Drive Systems (IJPEDS
), vol.
11
, p.
571
,
2020
.
15.
A.
Harigopal
and
Nithin
S.
, “
Assessment of State of Charge estimation techniques for Li-Ion battery pack
”, in
2020 International Conference on Smart Electronics and Communication (ICOSEC
),
2020
.
16.
Dr. M.
Ramu
,
Dr P. R.
Thyla
,
Raja
,
D. V.
Prabhu
,
C.
Vineeth
, and
Bheemappa
, “Effective Thermal Management System for Batteries in Electric Cars”,
PACE ANNUAL FORUM
2013
. Arts Center College of Design,
Pasadena, California
,
2013
17.
B. M.
Prabhakar
,
J.
Ramprabhakar
and
V.
Sailaja
, "
Estimation and controlling the state of charge in battery augmented photovoltaic system
,"
2016 Biennial International Conference on Power and Energy Systems: Towards Sustainable Energy (PESTSE
),
2016
, pp.
1
6
, doi: .
This content is only available via PDF.
You do not currently have access to this content.