Authors: Balaganesh.S, Mrs.S. Indhumathi,M.E, Dr.A.Shiny Pradeepa, M.E
Abstract: Electric vehicles rely heavily on battery performance, safety, and lifespan, making efficient battery management essential. Existing battery systems face drawbacks such as inaccurate state estimation, poor thermal management, cell imbalance, and limited real-time fault detection, leading to reduced efficiency and safety risks. A Battery Management and Monitoring System addresses these issues by continuously supervising battery parameters to ensure safe, reliable, and optimal EV operation. Therefore, this project proposes a smart, connected, and predictive solution for effective battery management in electric vehicles. The system utilizes both an ESP32 and a Raspberry Pi Pico as central controllers to enhance data processing and control capabilities. Sensors such as voltage, current, and temperature (DHT11) are used to continuously monitor the battery’s key parameters. The ESP32 handles IoT connectivity, transmitting real-time data to a cloud platform (like Blynk), and allowing users to remotely monitor battery status and control motor operations via the internet. Meanwhile, the Raspberry Pi Pico is employed to manage local data acquisition, signal processing, and protective control logic. This division ensures faster and more reliable responses to critical conditions. A relay driver and electronic relay are used to regulate the DC gear motor, ensuring optimal power management based on the sensed data. In case of abnormalities such as overvoltage, overcurrent, or overheating, the system can automatically trigger protective actions to prevent battery damage. This intelligent and connected solution not only improves operational efficiency and reliability but also promotes the advancement of sustainable electric vehicle technology through smart, dual-controller energy management. The combined use of ESP32 and Raspberry Pi Pico provides both robust cloud integration and precise local control, making the system highly responsive and reliable.
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