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首页> 外文会议>International Conference on Computer and Information Sciences >Li-Ion Battery SoH Estimation Based on the Event-Driven Sampling of Cell Voltage
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Li-Ion Battery SoH Estimation Based on the Event-Driven Sampling of Cell Voltage

机译：基于事件驱动的电池电压采样的锂离子电池SoH估计

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In modern grids the deployment of rechargeable batteries is exponentially increasing. The Battery Management Systems (BMSs) are used to achieve a longer battery life and to maximize its usefulness. Contemporary BMSs are complex, creating a greater overhead consumption on the battery. The purpose of this work is to improve the power efficiency of the modern BMSs. To this end the processes of level-crossing sensing and processing are used. The emphasis is on developing a reliable, efficient, and real-time technique for estimating battery cells’ state of health (SoH) by measuring their instantaneous voltages. Using an original event-driven approach, the SoH is approximated. Comparison of the designed system is performed with traditional counterpart. Results show, for the case of a 2 cells battery pack, an outperformance of 21.2 folds in terms of compression gain and computational efficiency while maintaining sufficient precision of the SoH estimation.
机译：在现代电网中，可再充电电池的部署呈指数增长。电池管理系统（BMS）用于延长电池寿命并最大程度地发挥其作用。当代的BMS非常复杂，在电池上产生更大的开销消耗。这项工作的目的是提高现代BMS的电源效率。为此，使用了跨越交叉感测和处理的过程。重点是开发一种可靠，高效且实时的技术，通过测量电池的瞬时电压来估算电池的健康状态（SoH）。使用原始的事件驱动方法，可以估算SoH。设计的系统与传统的系统进行比较。结果显示，对于2单元电池组，在压缩增益和计算效率方面表现优于21.2倍，同时保持了SoH估算的足够精度。

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