用于监测汽车锂基电池的新兴传感器技术和物理指导方法。

Xia Zeng, Maitane Berecibar
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引用次数: 0

摘要

随着汽车行业向电力推进的重大转变,对电池健康状况和潜在安全问题的可靠评估至关重要。这篇综述涵盖了传感器技术的进展,从机械和气体传感器到超声成像技术,这些技术可以深入了解锂离子电池的复杂结构和动力学。此外,我们探索了物理引导的机器学习方法与多传感器系统的集成,以提高电池建模和监测的准确性。讨论了这些多传感器系统在原型设计和扩展方面的挑战和机遇,强调了当前的局限性和未来的潜力。本研究的目的是全面概述未来汽车电池管理系统中传感器与物理引导方法相结合的现状、挑战和未来方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emerging sensor technologies and physics-guided methods for monitoring automotive lithium-based batteries.

As the automotive industry undergoes a major shift to electric propulsion, reliable assessment of battery health and potential safety issues is critical. This review covers advances in sensor technology, from mechanical and gas sensors to ultrasonic imaging techniques that provide insight into the complex structures and dynamics of lithium-ion batteries. In addition, we explore the integration of physics-guided machine learning methods with multi-sensor systems to improve the accuracy of battery modeling and monitoring. Challenges and opportunities in prototyping and scaling these multi-sensor systems are discussed, highlighting both current limitations and future potential. The purpose of this study is to provide a comprehensive overview of the current status, challenges, and future directions of combining sensors with physically guided methods for future vehicle battery management systems.

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