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A Health Monitoring Method Based on Multivariate State Estimation Technique

机译:一种基于多变量状态估计技术的健康监测方法

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The monitor of lithium-ion battery health is becoming a challenge because the performance of battery is effect by many environment factors. To address this problem, a new health monitor method based on Multivariate State Estimation Technique (MSET) and Sequential Probability Ratio Test (SPRT) is proposed in this paper. In order to demonstrate the performance gain of the method, a detailed experiment is performed based on a lithium-ion battery. By the comparison of performance parameters actual residuals and healthy residuals driven from the training data based on MSET, the fault detection can be implemented based oft the SPRT.
机译:锂离子电池健康的监视器正在成为一个挑战,因为电池的性能是通过许多环境因素的影响。为了解决这个问题,本文提出了一种基于多变量状态估计技术(MSET)和顺序概率比测试(SPRT)的新的健康监测方法。为了证明该方法的性能增益,基于锂离子电池进行详细实验。通过对基于MSET的训练数据驱动的实际残差和健康残留的实际残差和健康残差,可以基于SPRT实现故障检测。

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