电动汽车离子电池的传感器故障估计方法
Tianyu Lan1, Zhi-Wei Gao1, Haishuang Yin1
1Research Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163000, China.
Sensors (Basel, Switzerland)
|September 28, 2023
概括
这项研究引入了一种新的基于电动汽车电池传感器的基于模型的故障诊断方案. 它可以早期检测电压,电流和温度传感器故障,从而提高安全性和可靠性.
科学领域:
- 电气工程 电气工程
- 材料科学 材料科学 材料科学
- 汽车工程 汽车工程
背景情况:
- 电动汽车 (EV) 和离子电池 (LIB) 正在迅速发展.
- 电池的安全性和可靠性是LIBs关心的关键问题.
- 电池管理系统 (BMS) 依赖于准确的传感器数据以实现最佳性能.
研究的目的:
- 为LIBs开发经过验证的电热模型.
- 为电池传感器建立基于模型的故障诊断方案.
- 为了实现LIBs中传感器故障的早期检测.
主要方法:
- 使用描述符的比例和衍生观察者系统进行传感器诊断.
- 使用实验数据开发了LIB的验证电气和热模型.
- 实现了电压,电流和温度传感器故障的实时估计.
主要成果:
- 成功模拟了各种故障类型,以验证拟议的诊断方案.
- 演示了观察员系统能够实时估计传感器故障的能力.
- 使用实验电池数据验证了基于模型的方法的有效性.
结论:
- 拟议的基于模型的故障诊断方案有效检测LIB中的传感器故障.
- 早期故障检测可以提高电池管理系统的安全性和可靠性.
- 这种方法有助于推进更安全,更可靠的电动汽车.
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