CAN Interface Insights for Electric Vehicle Battery Recycling

IF 4.6 4区 化学 Q2 ELECTROCHEMISTRY Batteries Pub Date : 2024-05-07 DOI:10.3390/batteries10050158
Tero Niemi, Tero Kaarlela, Emilia Niittyviita, Ulla Lassi, J. Röning
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Abstract

Road transportation is a significant worldwide contributor to greenhouse gases, and electrifying the driveline of road vehicles is essential in overcoming the evident challenge of climate change. A sustainable transition to electric vehicles requires efficient and safe methods for recycling and repurposing used electric vehicle batteries. While various testing methods have been explored for assessing battery state of health and state of risk for recycling and reuse, a research gap exists concerning using data from integrated battery monitoring systems in the recycling process of electric vehicle batteries. This study addresses the research gap by presenting an approach to extract data from the monitoring system integrated into the battery using the automotive standard controller area network interface. In addition, methods to use this interface to ensure the optimal state of charge of the batteries for storage are presented. The benefits, challenges, and limitations set by the proprietary nature of the data to assess the state of risk and health of electric vehicle batteries for recycling and repurposing are presented, discussed, and evaluated. Finally, the influence of battery regulations and the battery passport proposal on electric vehicle battery recycling and repurposing are discussed to provide future perspectives.
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CAN 接口对电动汽车电池回收的启示
公路运输是全球温室气体的重要排放源,而公路车辆传动系统的电气化对于克服气候变化这一显而易见的挑战至关重要。要实现向电动汽车的可持续过渡,就必须采用高效、安全的方法对废旧电动汽车电池进行回收和再利用。虽然人们已经探索了各种测试方法来评估电池的健康状况以及回收和再利用的风险状况,但在电动汽车电池回收过程中使用来自集成电池监测系统的数据方面还存在研究空白。本研究针对这一研究空白,提出了一种利用汽车标准控制器区域网络接口从集成到电池中的监控系统中提取数据的方法。此外,还介绍了使用该接口确保电池处于最佳充电状态以进行存储的方法。此外,还介绍、讨论和评估了评估电动汽车电池回收和再利用的风险和健康状况的数据专有性质所带来的好处、挑战和限制。最后,讨论了电池法规和电池护照提案对电动汽车电池回收和再利用的影响,以提供未来展望。
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来源期刊
Batteries
Batteries Energy-Energy Engineering and Power Technology
CiteScore
4.00
自引率
15.00%
发文量
217
审稿时长
7 weeks
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