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Adaptive extended kalman filter based fault detection and isolation for a lithium-ion battery pack

机译:基于自适应扩展卡尔曼滤波器的锂离子电池组的故障检测和隔离

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To monitor the battery system, a well-designed battery management system with a set of current and voltage sensors is demanded to properly track the battery properties. It is imperative to design a reliable and robust diagnostic scheme in case of the employed sensors faults occurred. This paper presents a model-based fault diagnosis scheme to detect and isolate the faults of the current and voltage sensors applied in the series battery pack based on an adaptive extended kalman filter, and the robustness of the proposed diagnostic strategy is ensured. The diagnostic scheme is validated in the Matlab/Simulink, and the simulation results show the effectiveness of the proposed strategy in detecting and isolating various fault scenarios using the real-world driving cycles.
机译:为了监控电池系统,要求设计具有一组电流和电压传感器的精心设计的电池管理系统,以正确跟踪电池特性。 在采用的传感器故障发生故障时,必须设计可靠且稳健的诊断方案。 本文介绍了一种基于模型的故障诊断方案,用于检测和隔离基于适应性扩展卡尔曼滤波器的串联电池组中应用的电流和电压传感器的故障,并确保了所提出的诊断策略的鲁棒性。 在Matlab / Simulink中验证了诊断方案,仿真结果显示了使用现实世界驱动周期检测和隔离各种故障情景的策略的有效性。

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