Design of Battery management system for Residential applications

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2020 by IJETT Journal
Volume-68 Issue-3
Year of Publication : 2020
Authors : Poushali Pal, Devabalaji K. R, S. Priyadarshini
DOI :  10.14445/22315381/IJETT-V68I3P203S

Citation 

MLA Style: Poushali Pal, Devabalaji K. R, S. Priyadarshini  "Design of Battery management system for Residential applications" International Journal of Engineering Trends and Technology 68.3(2020):12-17.

APA Style:Poushali Pal, Devabalaji K. R, S. Priyadarshini. Design of Battery management system for Residential applications  International Journal of Engineering Trends and Technology, 68(3),12-17.

Abstract
Battery management system plays an important role for modern battery-powered application such as Electric vehicles, portable electronic equipment and storage for renewable energy sources. It also increases the life-cycle of the battery, battery state and efficiency. Monitoring the state of charge of the battery is a crucial factor for battery management system. This paper deals with monitoring the state of charge of the battery along with temperature, current for Solar panel fitted with battery for residential application. Microcontroller is used for controlling purpose, analog sensors are used for sensing the parameters of voltage, current. The information of the battery is given with tabular form and shown in photograph. Battery parameters are displayed with the LCD screen.

Reference

[1] Xiaosong Hu,Fei Feng, Kailong Liu et.al. “State estimation for advanced battery management: Key challenges and future trends” Renewable and Sustainable Energy Reviews, vol.114, 2019.
[2] C. Chen, K.L. Man, T.O. Ting et.al.” Design and Realization of a Smart Battery Management System” IMECS2016,March 14-16,2012,Hongkong.
[3] Markus Lelie ,Thomas Braun , Marcus Knips et.al.” Battery Management System Hardware Concepts:An Overview” Applied sciences, 30 March 2018.
[4] Rui Xiong, Linlin Li, Jinpeng Tian” Towards a smarter battery management system: A critical review on battery state of health monitoring methods” Journal of Power Sources vol.405,2018, pp.18–29.
[5] Sang Chon, Jon Beall” Intelligent battery management and charging for electric vehicles”.
[6] Elwer, Ghania, Gawad et.al.”Battery management systems for electric vehicle applications”.
[7] C. Chen, K.L. Man, T.O. Ting et.al.” Design and realization of a smart battery management system” IMECS 2012,March 14-16,2012,Hongkong.
[8] J. Ramprabu, B. Karunamoorthy” BMS: Efficient Handling of Battery using Battery Management System and Optimization technique of Battery Charging System in Electric Vehicles” International Journal of Pure and Applied Mathematics ,vol. 118, 2018, pp.265-276.
[9] Hengky K. Salim, Rodney A. Stewart, Oz Sahin et.al. “End-of-life management of solar photovoltaic and battery energy storage systems: A stakeholder survey in Australia “ Resources, Conservation and Recycling ,vol.150,2019.
[10] Mohammed Guezgouz, Jakub Jurasz, Bennaissa Bekkouche et.al.” Optimal hybrid pumped hydro-battery storage scheme for off-grid renewable energy systems” Energy Conversion and Management, vol.199,2019.
[11] R. Santhanapoongodi, Dr.V.Rajini” A New State of Charge Estimation Algorithm for Lead Acid Battery” 2016 International Conference on Computation of Power, Energy Information and Communication (ICCPEIC).
[12] L. Xu, J. P. Wang, and Q. S. Chen, “Kalman filtering state of charge estimation for battery management system based on a stochastic fuzzy neural network battery model,” Energy Conversion and Management, vol. 53, pp. 33–39, 2012.
[13] Shinya Sato , Atsuo Kawamura,”A New Estimation Method of State of Charge using Terminal Voltage and Internal Resistance for Lead Acid Battery,” IEEE Conference 2002.
[14] Shuo Pang,Jay Farrell, Jie Du and Matthew Barth,”Battery State-Of-Charge Estimation,” Proceedings of the American Control Conference June 25-27, 2001.
[15] Seonwoo Jeon, Jae-Jung Yun and Sungwoo Bae,”Comparative Study on the Battery State-of-Charge Estimation Method” Indian Journal of Science and Technology , Vol 8(26), IPL0524, October 2015
[16] F. Husnayain, A. R. Utomo, PS. Priambodo,” State of Charge Estimation for a Lead-Acid Battery Using Backpropagation Neural Network Method “IEEE International Conference on Electrical Engineering and Computer Science 24-25 November 2014, Bali, Indonesia.
[17] A.H.Anbuky and P.E.Pascoe,”VRLA battery State-of-charge estimation in telecommunication power Systems,” IEEE transactions on Industrial Electronics,vpl.47,pp.565-573,2000.

Keywords
Battery management system (BMS), Renewable energy sources (RES), Microcontroller.