• Gaurav Taulkar
• Sonali Jadhav
• Akshay Almale
• Abhishek Fule

Electric vehicles are rapidly gaining popularity due to their numerous advantages such as low maintenance, reduced emissions, and lower cost of ownership. However, the lack of infrastructure for charging stations, as well as the need for better battery management, are hindering their widespread adoption. To address these issues, a cloud-based EV battery management and charging station technology can be utilized. In this project, we propose to use a Raspberry Pi database, along with temperature, voltage, and current sensors, and cloud platforms to create a comprehensive battery management system. The system's primary objective is to log all information about the battery level and display it to the user in real-time. The system will collect data on various parameters such as voltage, current, and power consumption, and will provide real-time tracking via GPS navigation. If the battery level is too low, the system will automatically notify the user via the IoT platform, indicating the need for charging. The system will also display the nearest charging station relative to the EV's current location, which will help users find charging stations quickly and conveniently. Overall, the proposed system is designed to provide a comprehensive solution for EV battery management, making it easier for users to monitor their EVs' battery levels and locate charging stations when needed. The use of cloud-based technology and the integration of various sensors and platforms will ensure the system's reliability and accuracy, while also improving the overall user experience.

Battery Management system, Electric vehicle, Internet of things, Battery, Location.

"EV Charging Station Location Detection System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.222-226, May-2023, Available :http://www.jetir.org/papers/JETIRFX06038.pdf

"EV Charging Station Location Detection System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pp222-226, May-2023, Available at : http://www.jetir.org/papers/JETIRFX06038.pdf