TY - GEN
T1 - Simulation of Charging of Electric Vehicle Using Hybrid Energy Sources with IOT
AU - Chaudhary, Sunil Kumar
AU - Singh, Anurag
AU - Prasad, Aryan
AU - Kumar, Praveen
AU - Verma, Gargi
AU - Gupta, Anushka
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In this paper, a charging system is designed which is fitted in electric vehicle for efficiently charging of the battery to reduce dependency on grid which is done with the help of renewable energy sources i.e. solar as a source and wind as a source. The monitoring, controlling and operation of the battery is done by IOT and AI which ensures the optimal performance, efficiency, safety, charging and discharging patterns of the battery. The IOT incorporates with various sensors to show the current, voltage and temperature readings to ensure the smooth charging of battery. The AI is implemented by using various algorithms based on history (previous) and present data which controls the discharging and charging patterns of the battery, charging of the battery with the source which has abundance in environment and protection from high temperature, overvoltage and overcurrent conditions. By addressing the issues of grid congestion and variable energy sources, this all-encompassing solution not only promotes sustainable mobility but also help users in a new era of intelligent and environmentally friendly electric vehicle charging infrastructure.
AB - In this paper, a charging system is designed which is fitted in electric vehicle for efficiently charging of the battery to reduce dependency on grid which is done with the help of renewable energy sources i.e. solar as a source and wind as a source. The monitoring, controlling and operation of the battery is done by IOT and AI which ensures the optimal performance, efficiency, safety, charging and discharging patterns of the battery. The IOT incorporates with various sensors to show the current, voltage and temperature readings to ensure the smooth charging of battery. The AI is implemented by using various algorithms based on history (previous) and present data which controls the discharging and charging patterns of the battery, charging of the battery with the source which has abundance in environment and protection from high temperature, overvoltage and overcurrent conditions. By addressing the issues of grid congestion and variable energy sources, this all-encompassing solution not only promotes sustainable mobility but also help users in a new era of intelligent and environmentally friendly electric vehicle charging infrastructure.
KW - AI
KW - Current and Voltage Monitoring
KW - Efficient Charging
KW - IOT
KW - Overheating Protection
UR - http://www.scopus.com/inward/record.url?scp=85193792479&partnerID=8YFLogxK
U2 - 10.1109/ICRITO61523.2024.10522228
DO - 10.1109/ICRITO61523.2024.10522228
M3 - Conference contribution
AN - SCOPUS:85193792479
T3 - 2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2024
BT - 2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2024
A2 - Shukla, Balvinder
A2 - Agarwal, Rekha
A2 - Khatri, Sunil Kumar
A2 - Soni, K.M.
A2 - Singh, Ajay Vikram
A2 - Jain, Sarika
A2 - Sindhwani, Nidhi
A2 - Chaudhary, Alka
A2 - Gautam, Ritu
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024
Y2 - 14 March 2024 through 15 March 2024
ER -