CAN IoT and FreeRTOS for High-Resolution Data Collection in Battery Electric Buses: A Real Case Study in Public Transportation

This paper presents the development and validation of an innovative CAN-based IoT device designed primarily for high-resolution data collection in urban battery electric buses (BEB), facilitating the advancement of precise predictive models in smart transportation systems. Utilizing the ESP-WROOM-32 module with multi-core processing capabilities and the FreeRTOS operating system, the device excels in capturing fine-grained data critical for enhanced predictive analytics. The SAE J1939 protocol enables seamless integration with the electric CAN BUS system, ensuring comprehensive data acquisition of key parameters such as voltage, current, state of charge (SOC), state of health (SOH), battery temperature, and motor RPM. Over four months of testing at UNICAMP, the device demonstrated exceptional reliability, with 96.10% of Power Battery data falling within the expected range and 90 % to 93 % adherence for other data groups. It maintained robust connectivity and data integrity, even during operational interruptions. While offering real-time monitoring as an added benefit, the primary contribution of this system lies in its capacity to support the development of highly accurate pre-dictive maintenance models and operational trend forecasting. This paves the way for more intelligent and sustainable urban transportation solutions.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/sbesc65055.2024.10771929
Citations
4
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.81
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article

CAN IoT and FreeRTOS for High-Resolution Data Collection in Battery Electric Buses: A Real Case Study in Public Transportation

Madson C. de Almeida, Flávio Tonioli Mariotto, Hernan R. Ullón, Thonny E. Mota
4 citations
Advanced Battery Technologies Research
0.81
article

CAN IoT and FreeRTOS for High-Resolution Data Collection in Battery Electric Buses: A Real Case Study in Public Transportation

Madson C. de Almeida, Flávio Tonioli Mariotto, Hernan R. Ullón, Thonny E. Mota
article en
4 citations

Abstract

This paper presents the development and validation of an innovative CAN-based IoT device designed primarily for high-resolution data collection in urban battery electric buses (BEB), facilitating the advancement of precise predictive models in smart transportation systems. Utilizing the ESP-WROOM-32 module with multi-core processing capabilities and the FreeRTOS operating system, the device excels in capturing fine-grained data critical for enhanced predictive analytics. The SAE J1939 protocol enables seamless integration with the electric CAN BUS system, ensuring comprehensive data acquisition of key parameters such as voltage, current, state of charge (SOC), state of health (SOH), battery temperature, and motor RPM. Over four months of testing at UNICAMP, the device demonstrated exceptional reliability, with 96.10% of Power Battery data falling within the expected range and 90 % to 93 % adherence for other data groups. It maintained robust connectivity and data integrity, even during operational interruptions. While offering real-time monitoring as an added benefit, the primary contribution of this system lies in its capacity to support the development of highly accurate pre-dictive maintenance models and operational trend forecasting. This paves the way for more intelligent and sustainable urban transportation solutions.

Universidade Estadual de Campinas (UNICAMP) (BR)
Openalex Percentile: Top 28%
Advanced Battery Technologies Research
0.81
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CAN IoT and FreeRTOS for High-Resolution Data Collection in Battery Electric Buses: A Real Case Study in Public Transportation — Madson C. de Almeida, Flávio Tonioli Mariotto, et al. · (2024) | TGRS Research Map | TGRS