ARCHIVES
Research Article
The Adoption of Internet of Things to Monitor Electric Vehicle’s Battery and Implementing Early Warning System
Khadar Basha N1
Bhuvaneshwari V M2
1Department of ECE, Assistant Professor, Dhanalakshmi Srinivasan Engineering College (Autonomous), Perambalur, TN, India. 2Department of ECE, PG Student, Dhanalakshmi Srinivasan Engineering College (Autonomous), Perambalur, TN, India.
Published Online: November-December 2022
Pages: 268-270
Cite this article
No DOIReferences
1. K. Guo Dengfeng, Xu Shan, “The Internet of Things hold up Smart Grid networking technology,” North China Electr., vol. 2, pp. 59–63,
2010.
2. ITU, “The Internet of Things,” Itu Internet Rep. 2005, p. 212, 2005.
3. X. Fang, S. Misra, G. Xue, and D. Yang, “Smart Grid — The New and Improved Power Grid: A Survey,” IEEE Commun. Surv.
Tutorials, vol. 14, no. 4, pp. 944–980, 2012.
4. B. P. Roberts and C. Sandberg, “The role of energy storage in development of smart grids,” in Proceedings of the IEEE, 2011, vol. 99,
no. 6, pp. 1139–1144.
5. R. Liu, L. Dow, and E. Liu, “A survey of PEV impacts on electric utilities,” in IEEE PES Innovative Smart Grid Technologies
Conference Europe, ISGT Europe, 2011.
6. Z. Rao, S. Wang, and G. Zhang, “Simulation and experiment of thermal energy management with phase change material for ageing
LiFePO4 power battery,” Energy Convers. Manag., vol. 52, no. 12, pp. 3408–3414, 2011.
7. N. Watrin, B. Blunier, and A. Miraoui, “Review of adaptive systems for lithium batteries state-of-charge and state-of-health estimation,”
in 2012 IEEE Transportation Electrification Conference and Expo, ITEC 2012, 2012.
8. S. Piller, M. Perrin, and A. Jossen, “Methods for state-of-charge determination and their applications,” in Journal of Power Sources,
2001, vol. 96, no. 1, pp. 113–120.
9. L. Lu, et.al., “A review on the key issues for lithium-ion battery management in electric vehicles,” Journal of Power Sources, vol. 226.
pp. 272–288, 2013.
10. M. Charkhgard and M. Farrokhi, “State-of-charge estimation for lithium-ion batteries using neural networks and EKF,” IEEE Trans.
Ind. Electron., vol. 57, no. 12, pp. 4178–4187, 2010.
11. G. Y. Y. Ding-xuan, “SOC estimation of Lithium-ion battery based on Kalman filter algorithm,” in 2nd International Conference on
Computer Science and Electronics Engineering (ICCSEE), 2013.
12. C. M. and Y. H. K.S. Ng, Y.F Huang, “An enhanced coulomb counting method for estimating state-of-charge and state-of-health of lead-
acid batteries,” in 31st International Telecommunications Energy Conference (INTELEC 2009).
2010.
2. ITU, “The Internet of Things,” Itu Internet Rep. 2005, p. 212, 2005.
3. X. Fang, S. Misra, G. Xue, and D. Yang, “Smart Grid — The New and Improved Power Grid: A Survey,” IEEE Commun. Surv.
Tutorials, vol. 14, no. 4, pp. 944–980, 2012.
4. B. P. Roberts and C. Sandberg, “The role of energy storage in development of smart grids,” in Proceedings of the IEEE, 2011, vol. 99,
no. 6, pp. 1139–1144.
5. R. Liu, L. Dow, and E. Liu, “A survey of PEV impacts on electric utilities,” in IEEE PES Innovative Smart Grid Technologies
Conference Europe, ISGT Europe, 2011.
6. Z. Rao, S. Wang, and G. Zhang, “Simulation and experiment of thermal energy management with phase change material for ageing
LiFePO4 power battery,” Energy Convers. Manag., vol. 52, no. 12, pp. 3408–3414, 2011.
7. N. Watrin, B. Blunier, and A. Miraoui, “Review of adaptive systems for lithium batteries state-of-charge and state-of-health estimation,”
in 2012 IEEE Transportation Electrification Conference and Expo, ITEC 2012, 2012.
8. S. Piller, M. Perrin, and A. Jossen, “Methods for state-of-charge determination and their applications,” in Journal of Power Sources,
2001, vol. 96, no. 1, pp. 113–120.
9. L. Lu, et.al., “A review on the key issues for lithium-ion battery management in electric vehicles,” Journal of Power Sources, vol. 226.
pp. 272–288, 2013.
10. M. Charkhgard and M. Farrokhi, “State-of-charge estimation for lithium-ion batteries using neural networks and EKF,” IEEE Trans.
Ind. Electron., vol. 57, no. 12, pp. 4178–4187, 2010.
11. G. Y. Y. Ding-xuan, “SOC estimation of Lithium-ion battery based on Kalman filter algorithm,” in 2nd International Conference on
Computer Science and Electronics Engineering (ICCSEE), 2013.
12. C. M. and Y. H. K.S. Ng, Y.F Huang, “An enhanced coulomb counting method for estimating state-of-charge and state-of-health of lead-
acid batteries,” in 31st International Telecommunications Energy Conference (INTELEC 2009).
Related Articles
2022
A Review on Bamboo Reinforced Concrete Beam
2022
FARMERS AGRICULTURAL PORTAL
2022
Sentiment Analysis of Religious Tweets
2022
Enhancement of beam strength by using bamboo as reinforcement in place of steel bars
2022
A Review on Anomaly Detection using PYOD Package
2022
Traffic Rule Violation Detection system
Share Article
Or copy link
https://theijire.com/archives/the-adoption-of-internet-of-things-to-monitor-electric-vehicles-battery-and-implementing-early-warning-system
*Instagram doesn't support direct link sharing from web. Copy the link and share it in your Instagram story or post.