为解决混合动力汽车(hybrid electric vehicle,HEV)模式切换过程中电机MG2非失效故障问题,提高整车的安全性、动力性与舒适性,以一种功率分流式HEV为研究对象,提取电机MG2故障发生后40ms内的整车冲击度与车速跟踪误差信息作为特征量,采...为解决混合动力汽车(hybrid electric vehicle,HEV)模式切换过程中电机MG2非失效故障问题,提高整车的安全性、动力性与舒适性,以一种功率分流式HEV为研究对象,提取电机MG2故障发生后40ms内的整车冲击度与车速跟踪误差信息作为特征量,采用贝叶斯优化方法自动搜索最优超参数点,搭建故障诊断模型,并设计包含补偿系数调节模块和电机MG1补偿模块的自适应容错控制器。仿真结果表明:所提电机非失效故障诊断与自适应容错控制方法具有较好的可行性、准确性和容错效果。展开更多
This article considers estimation of the unknown parameters for the compound Rayleigh distribution (CRD) based on a new life test plan called a progressive first failure-censored plan introduced by Wu and Kus (2009). ...This article considers estimation of the unknown parameters for the compound Rayleigh distribution (CRD) based on a new life test plan called a progressive first failure-censored plan introduced by Wu and Kus (2009). We consider the maximum likelihood and Bayesian inference of the unknown parameters of the model, as well as the reliability and hazard rate functions. This was done using the conjugate prior for the shape parameter, and discrete prior for the scale parameter. The Bayes estimators hav been obtained relative to both symmetric (squared error) and asymmetric (LINEX and general entropy (GE)) loss functions. It has been seen that the symmetric and asymmetric Bayes estimators are obtained in closed forms. Also, based on this new censoring scheme, approximate confidence intervals for the parameters of CRD are developed. A practical example using real data set was used for illustration. Finally, to assess the performance of the proposed estimators, some numerical results using Monte Carlo simulation study were reported.展开更多
文摘为解决混合动力汽车(hybrid electric vehicle,HEV)模式切换过程中电机MG2非失效故障问题,提高整车的安全性、动力性与舒适性,以一种功率分流式HEV为研究对象,提取电机MG2故障发生后40ms内的整车冲击度与车速跟踪误差信息作为特征量,采用贝叶斯优化方法自动搜索最优超参数点,搭建故障诊断模型,并设计包含补偿系数调节模块和电机MG1补偿模块的自适应容错控制器。仿真结果表明:所提电机非失效故障诊断与自适应容错控制方法具有较好的可行性、准确性和容错效果。
文摘This article considers estimation of the unknown parameters for the compound Rayleigh distribution (CRD) based on a new life test plan called a progressive first failure-censored plan introduced by Wu and Kus (2009). We consider the maximum likelihood and Bayesian inference of the unknown parameters of the model, as well as the reliability and hazard rate functions. This was done using the conjugate prior for the shape parameter, and discrete prior for the scale parameter. The Bayes estimators hav been obtained relative to both symmetric (squared error) and asymmetric (LINEX and general entropy (GE)) loss functions. It has been seen that the symmetric and asymmetric Bayes estimators are obtained in closed forms. Also, based on this new censoring scheme, approximate confidence intervals for the parameters of CRD are developed. A practical example using real data set was used for illustration. Finally, to assess the performance of the proposed estimators, some numerical results using Monte Carlo simulation study were reported.
