化学电池可靠性增长分析

发布时间：2018-06-17 17:15

本文选题：化学电池 + 可靠性增长　；参考：《北京理工大学》2015年硕士论文

【摘要】：化学电池在通讯、汽车、军事、航空航天等领域具有广泛的应用，随着其应用范围和应用程度的不断深入，电池可靠性得到了越来越高的重视。本文以此为背景，研究了可靠性增长理论在电池可靠性增长上的应用。本文首先介绍了可靠性增长的基本概念以及可靠性增长的Duane模型和AMSAA模型，重点研究单台产品的AMSAA模型、多台产品的AMSAA-BISE模型和多台产品的AMSAA模型。然后介绍了锂离子电池的结构以及可靠性增长过程中常用的分析方法，这些方法可以有效地提高电池的可靠性。由于不易获得化学电池的可靠性增长数据，，本文提出利用逆变换技术和威布尔过程来模拟电池的可靠性增长数据。然后利用Matlab软件分别对时间截尾数据和故障截尾数据进行模拟，对单台产品和多台产品的数据进行计算及分析，并讨论了模型参数变化对故障率的影响。由于Duane模型和AMSAA模型都是基于产品故障时间的可靠性增长模型，它们只适合处理基于TAAF模式的连续时间的可靠性增长。而对于分阶段的延缓纠正的可靠性增长模式，仅仅使用基于时间的可靠性增长模型无法充分使用各阶段已有的试验信息，在应用上存在缺陷。针对上述问题，本文结合贝叶斯方法，提出了电池分阶段的Bayes可靠性增长模型。传统的可靠性增长评估方法使评估结果偏于保守，而Bayes可靠性增长模型考虑了各阶段的验前信息和验后信息，可以动态评估电池的可靠性增长过程，并对电池的可靠性水平进行预测，评估结果更加符合实际。
[Abstract]:Chemical battery has been widely used in the fields of communication, automobile, military, aerospace and so on. With the development of its application range and application degree, the reliability of battery has been paid more and more attention. In this paper, the application of reliability growth theory to battery reliability growth is studied. In this paper, the basic concept of reliability growth and the Duane model and AMSAA model of reliability growth are introduced, and the AMSAA model of single product, AMSAA-BISE model of multiple products and AMSAA model of multiple products are studied. Then the structure of lithium ion battery and the commonly used analysis methods in the process of reliability growth are introduced. These methods can effectively improve the reliability of the battery. Because it is difficult to obtain the reliability growth data of the chemical battery, this paper proposes to simulate the reliability growth data of the cell by using the inverse transformation technique and the Weibull process. Then the time truncated data and the fault truncated data are simulated by Matlab software, the data of single product and multiple products are calculated and analyzed, and the influence of model parameters on failure rate is discussed. Because both Duane model and AMSAA model are reliability growth models based on product failure time, they are only suitable to deal with the reliability growth of continuous time based on TAAF mode. However, the time-based reliability growth model can not make full use of the experimental information of each stage, and there are some defects in the application of the time-based reliability growth model. In order to solve the above problems, a Bayesian reliability growth model is proposed in this paper. The traditional reliability growth evaluation method makes the evaluation results conservative, while the Bayes reliability growth model takes into account the prior and posterior information of each stage, so it can dynamically evaluate the reliability growth process of the battery. The reliability level of the battery is predicted, and the evaluation results are more in line with the reality.
【学位授予单位】：北京理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TM911

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