CAN Based Battery Monitoring and Protection System with IoT Remote Dashboard for Electric Vehicle Applications

Abstract

This paper presents a Controller Area Network (CAN) based battery monitoring and protection system with an Internet-of-Things (IoT) remote dashboard, developed for electric vehicle applications and targeted at an eBAJA Electric All-Terrain Vehicle (EATV). The system is implemented as a distributed two-node architecture in which both nodes use an ESP32 microcontroller interfaced with an MCP2515 stand-alone CAN controller over SPI, operating at a 500 kbps CAN bit-rate with an 8 MHz oscillator. The transmitting node (Node 1) acquires battery pack voltage, temperature using an LM35 sensor, and current using a Hall-effect current-sensor module, computes the State of Charge (SOC) from a linear voltage mapping, assigns a fixed State of Health (SOH), and transmits the five parameters in a single 8-byte CAN frame with identifier 0x101 once per second. The receiving node (Node 2) decodes the frame and presents the data on a 20×4 I2C character LCD and on the Arduino serial monitor. The measured parameters are also published to a Blynk IoT dashboard for remote monitoring. A prototype battery of three series-connected lithium-ion cells (3.7 V, 2 Ah each, approximately 12 V pack) was used for bench validation, and a separate pulse-frequency motor-speed measurement routine was tested. Experimental outputs from the LCD, serial monitor, IoT dashboard, and a commercial smart-BMS application are presented and discussed. Available project outputs are presented and discussed qualitatively due to limited recorded datasets.

Introduction

This study presents a CAN-based Battery Monitoring and Protection System with IoT integration for an eBAJA Electric All-Terrain Vehicle (EATV). Electric vehicles require continuous monitoring of battery parameters such as voltage, current, temperature, State of Charge (SOC), and State of Health (SOH) to ensure safe and efficient operation. To achieve reliable communication in the harsh environment of an off-road vehicle, the system employs the Controller Area Network (CAN) bus, known for its robustness, noise immunity, and multi-node communication capability.

The proposed architecture consists of two ESP32 microcontroller nodes connected through MCP2515 CAN controllers. The transmitting node acquires battery voltage, current, and temperature data using dedicated sensors, calculates SOC and SOH, and sends the information over the CAN bus at 500 kbps. The receiving node decodes the CAN messages and displays the parameters on a 20×4 LCD display and serial monitor. Simultaneously, the data are uploaded to a Blynk IoT dashboard, enabling remote monitoring through cloud connectivity.

A laboratory-scale prototype battery pack comprising three lithium-ion cells (12 V, 2 Ah) was used to validate the monitoring framework. Since the actual 72 V, 80 Ah eBAJA battery pack involved proprietary hardware complexities, it was not directly integrated into the experimental setup. The system successfully monitored voltage, current, temperature, SOC, and SOH while demonstrating protection functionality through a relay-based load disconnection mechanism under high-temperature conditions.

In addition to battery monitoring, a motor-speed monitoring subsystem was implemented using interrupt-based pulse counting techniques. The system measured pulse frequency and converted it into rotational speed (RPM), achieving speeds of approximately 5486 RPM during testing.

Experimental results confirmed reliable CAN communication between the ESP32 nodes, consistent display of battery parameters on the LCD and IoT dashboard, and successful implementation of temperature-based protection. The observed values included approximately 11 V battery voltage, 35°C temperature, 71% SOC, and 100% SOH. The system demonstrated the feasibility of combining CAN communication and IoT technologies for distributed battery monitoring in electric vehicles.

Key advantages of the system include reduced wiring complexity, scalability, real-time local and remote monitoring, enhanced battery safety, modular design, and low implementation cost. However, limitations include validation on a prototype battery instead of the actual vehicle battery, simplified SOC estimation, placeholder SOH calculation, lack of cell-level monitoring, and absence of historical cloud analytics.

Future enhancements include integration with the actual eBAJA battery pack, advanced SOC/SOH estimation algorithms, predictive maintenance using machine learning, cloud-based data logging, GPS tracking, motor-controller CAN integration, and comprehensive vehicle diagnostics for full-scale electric vehicle deployment.

Conclusion

A CAN-based battery monitoring and protection system with an IoT remote dashboard was implemented and tested for electric vehicle application, targeting an eBAJA Electric All-Terrain Vehicle. The system uses two ESP32 nodes communicating through MCP2515 CAN controllers at 500 kbps. The transmitting node acquires voltage, temperature, and current, computes SOC and reports SOH, and sends the parameters in an 8-byte CAN frame with identifier 0x101; the receiving node decodes the frame and displays the data on a 20×4 I2C LCD and the serial monitor, while the parameters are also published to a Blynk dashboard. Bench testing on a three-cell lithium-ion prototype confirmed correct CAN transfer and consistent display across all interfaces, an observed temperature-fault “LOAD OFF” response, a pulse-based motor-speed measurement, and monitoring of the 20-cell vehicle pack with a commercial smart-BMS application. The results demonstrate a working distributed monitoring framework that can be extended with firmware-based protection and higher-resolution data handling.

References

[1] R. Bosch GmbH, “CAN Specification, Version 2.0,” Stuttgart, Germany, 1991. [2] ISO 11898-1:2015, “Road vehicles — Controller area network (CAN) — Part 1: Data link layer and physical signalling,” International Organization for Standardization, 2015. [3] Espressif Systems, “ESP32 Series Datasheet,” Espressif Systems, 2023. [4] Microchip Technology Inc., “MCP2515 Stand-Alone CAN Controller with SPI Interface Datasheet,” 2019. [5] Texas Instruments, “LM35 Precision Centigrade Temperature Sensors Datasheet,” 2017. [6] Allegro MicroSystems, “ACS712 Fully Integrated, Hall-Effect-Based Linear Current Sensor IC Datasheet,” 2017. [7] L. Lu, X. Han, J. Li, J. Hua, and M. Ouyang, “A review on the key issues for lithium-ion battery management in electric vehicles,” Journal of Power Sources, vol. 226, pp. 272–288, 2013. [8] H. Rahimi-Eichi, U. Ojha, F. Baronti, and M.-Y. Chow, “Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles,” IEEE Industrial Electronics Magazine, vol. 7, no. 2, pp. 4–16, 2013. [9] M. Brandl et al., “Batteries and battery management systems for electric vehicles,” in Proc. Design, Automation & Test in Europe Conference (DATE), 2012, pp. 971–976. [10] Blynk Inc., “Blynk IoT Platform Documentation,” Blynk Inc. [Online].

Copyright

Copyright © 2026 Mrunal Ravindra Dhawade, Prajwal Laxman Godage, Dipak Santosh Kulwade, Dr. Rohit Gawade. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.