Autor(es)

Mota, Thonny E. ; Ullon, Hernan R. ; Mariotto, Flavio T. ; de Almeida, Madson C.

• Tipo de documento: Artigo Científico
• Fonte: 2024 XIV BRAZILIAN SYMPOSIUM ON COMPUTING SYSTEMS ENGINEERING, SBESC; v. N/A, p. 6-pg., 2024-01-01.

Resumo

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 predictive maintenance models and operational trend forecasting. This paves the way for more intelligent and sustainable urban transportation solutions. (AU)

• Processo FAPESP: 21/11380-5 - CPTEn - Centro Paulista de Estudos da Transição Energética
• Beneficiário: Luiz Carlos Pereira da Silva
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Ciência para o Desenvolvimento