摘要
Electric vehicles (EV) feature detailed monitoring and control over the CAN bus. Some of this data is made available to users on the On-Board Diagnostic version II (OBDII) bus thus providing an opportunity for large scale high-frequency data collection. This paper introduces a connected monitoring system for OBDII equipped vehicles. The system comprises a low cost hardware design and monitoring algorithms designed to optimize the number of variables collected and their collection frequency. The algorithm aims at collecting a high quantity of Battery Management System (BMS) data in electric vehicles together with power-usage data to enable short and long term estimation for battery state of health (SOH) and state of charge (SOC). The proposed system has been implemented and tested on a Nissan Leaf and lead to the acquisition of 1.7 million records over 120 hours of driving.
原文 | English |
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頁(從 - 到) | 885-888 |
頁數 | 4 |
期刊 | Proceedings - IEEE Consumer Communications and Networking Conference, CCNC |
DOIs | |
出版狀態 | Published - 2022 |
事件 | 19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022 - Virtual, Online, United States 持續時間: 8 1月 2022 → 11 1月 2022 |