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Stochastic Knock Control with Beta Distribution Learning for Gasoline Engines

机译:带有汽油发动机的Beta分布学习的随机爆震控制

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Knock phenomenon as a stochastic process requires feedback control for its relation to engine efficiency, noise and cylinder damage. In this paper, a knock probability estimation method using Bayes’ updating rule and beta distribution is proposed based on the independent and identically distributed (iid) characteristic analysis of the knock event sequence. A stochastic control algorithm using the estimation method and likelihood ratio test is also proposed. The proposed control algorithm is validated on a production spark ignition engine and shows the ability to maintain knock probability close to the target.
机译:爆震现象是随机过程,因此需要反馈控制,因为它与发动机效率,噪音和气缸损坏有关。本文基于对爆震事件序列的独立且均匀分布(iid)特征分析,提出了一种使用贝叶斯更新规则和β分布的爆震概率估计方法。还提出了一种使用估计方法和似然比检验的随机控制算法。所提出的控制算法在生产的火花点火发动机上得到了验证,并显示了保持爆震概率接近目标的能力。

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