在电动汽车中使用物联网,区块链和机器学习的智能电池管理.
1Department of Electrical and Electronics Engineering, Sri Ramakrishna Engineering College, Coimbatore, India. kavithaduraiswamy@gmail.com.
Scientific reports
|October 29, 2025
概括
本研究介绍了通过整合物联网 (IoT) 和区块链技术为电动汽车 (EV) 提供增强的电池管理系统 (BMS). 新系统准确地检测到附近的充电站,并确保安全的交易,提高电动汽车的效率.
科学领域:
- 电气工程 电气工程
- 计算机科学 计算机科学
- 可持续能源 可持续能源
背景情况:
- 电动汽车 (EV) 面临着电池续航里程有限和充电基础设施可用性的挑战.
- 电池管理系统 (BMS) 对电动汽车电池的性能,效率和寿命至关重要.
- 整合物联网 (IoT) 和区块链 (BC) 提供了增强电动汽车电池管理和安全交易的潜力.
研究的目的:
- 为使用物联网,区块链和机器学习 (ML) 的电动汽车开发先进的BMS模型.
- 提高电动汽车的能源效率和电池状态评估.
- 确保电动汽车用户和充电站之间的安全数据存储和金融交易.
主要方法:
- 物联网传感器收集了电动汽车数据 (充电水平,距离,位置).
- 极端梯度提升 (XGBoost) 分类的收费成本.
- 灰狼优化 (GWO) 确定了充电站的最佳位置,时间和空间.
- 一个允许的区块链与同态加密 (HE) 保护数据和交易.
主要成果:
- 开发的BMS模型在检测附近充电站时实现了97.36%的准确率.
- 该系统保持了35毫秒的通信开销,比现有模型有14%的改进.
- 确保了安全和防改的数据存储和交易处理.
结论:
- 物联网,区块链和ML的整合显著增强了EV BMS的功能.
- 拟议的模型解决了电动汽车收费,可访问性和安全性的关键挑战.
- 这种方法为未来的电动移动提供了可扩展和安全的解决方案.
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