As an emergency and auxiliary power source for aircraft,lithium(Li)-ion batteries are important components of aerospace power systems.The Remaining Useful Life(RUL)prediction of Li-ion batteries is a key technology to...As an emergency and auxiliary power source for aircraft,lithium(Li)-ion batteries are important components of aerospace power systems.The Remaining Useful Life(RUL)prediction of Li-ion batteries is a key technology to ensure the reliable operation of aviation power systems.Particle Filter(PF)is an effective method to predict the RUL of Li-ion batteries because of its uncertainty representation and management ability.However,there are problems that particle weights cannot be updated in the prediction stage and particles degradation.To settle these issues,an innovative technique of F-distribution PF and Kernel Smoothing(FPFKS)algorithm is proposed.In the prediction stage,the weights of the particles are dynamically updated by the F kernel instead of being fixed all the time.Meanwhile,a first-order independent Markov capacity degradation model is established.Moreover,the kernel smoothing algorithm is integrated into PF,so that the variance of the parameters of capacity degradation model keeps invariant.Experiments based on NASA battery data sets show that FPFKS can be excellently applied to RUL prediction of Liion batteries.展开更多
In this article, the true model of sizep is considered. The importance of the independent variables will be studied. The model by dropping independent variable one at a time is called a reduced model, and the size of ...In this article, the true model of sizep is considered. The importance of the independent variables will be studied. The model by dropping independent variable one at a time is called a reduced model, and the size of the model is p-1. The non-centrality quantity is employed to measure the strength of influence on the true model for the independent variable dropped. The larger influence is defined to be more important in the true model. In this article, the goal is ranking the importance of the independent variables to study the structure of the models. It is important in the practical application. The confidence interval approach is used to rank the degrees of the influence of the independent variables in linear models and achieve the goal. An illustrative example is given, and the modeling procedure is studied to check the assumptions step by step in this example to make sure the assumptions satisfied in the true model. As a result, the proposed method can be used efficiently.展开更多
With the upper bound of Kullback-Leibler distance between a matrix variate Beta-distri- bution and a normal distribution, this paper gives the conditions under which a matrix-variate Beta- distribution will approach u...With the upper bound of Kullback-Leibler distance between a matrix variate Beta-distri- bution and a normal distribution, this paper gives the conditions under which a matrix-variate Beta- distribution will approach uniformly and asymptotically a normal distribution.展开更多
We analyzed the performance of a freespace optical(FSO)system in this study,considering the combined effects of atmospheric turbulence,fog absorption,and pointing errors.The impacts of atmospheric turbulence and foggy...We analyzed the performance of a freespace optical(FSO)system in this study,considering the combined effects of atmospheric turbulence,fog absorption,and pointing errors.The impacts of atmospheric turbulence and foggy absorption were modeled using the Fisher-Snedecor F distribution and the Gamma distribution,respectively.Next,we derived the probability density function(PDF)and cumulative probability density function of the optical system under these combined effects.Based on these statistical findings,closed-form expressions for various system metrics,such as outage probability,average bit error rate(BER),and ergodic capacity,were derived.Furthermore,we used a deep neural network(DNN)to predict the ergodic capacity of the system,achieving reduced running time and improved accuracy.Finally,the accuracy of the prediction results was validated by comparing them with the analytical results.展开更多
基金co-supported by Aeronautical Science Foundation of China (No. 20183352030)Fund Project of Equipment Pre-research Field of China (No. JZX7Y20190243016301)
文摘As an emergency and auxiliary power source for aircraft,lithium(Li)-ion batteries are important components of aerospace power systems.The Remaining Useful Life(RUL)prediction of Li-ion batteries is a key technology to ensure the reliable operation of aviation power systems.Particle Filter(PF)is an effective method to predict the RUL of Li-ion batteries because of its uncertainty representation and management ability.However,there are problems that particle weights cannot be updated in the prediction stage and particles degradation.To settle these issues,an innovative technique of F-distribution PF and Kernel Smoothing(FPFKS)algorithm is proposed.In the prediction stage,the weights of the particles are dynamically updated by the F kernel instead of being fixed all the time.Meanwhile,a first-order independent Markov capacity degradation model is established.Moreover,the kernel smoothing algorithm is integrated into PF,so that the variance of the parameters of capacity degradation model keeps invariant.Experiments based on NASA battery data sets show that FPFKS can be excellently applied to RUL prediction of Liion batteries.
文摘In this article, the true model of sizep is considered. The importance of the independent variables will be studied. The model by dropping independent variable one at a time is called a reduced model, and the size of the model is p-1. The non-centrality quantity is employed to measure the strength of influence on the true model for the independent variable dropped. The larger influence is defined to be more important in the true model. In this article, the goal is ranking the importance of the independent variables to study the structure of the models. It is important in the practical application. The confidence interval approach is used to rank the degrees of the influence of the independent variables in linear models and achieve the goal. An illustrative example is given, and the modeling procedure is studied to check the assumptions step by step in this example to make sure the assumptions satisfied in the true model. As a result, the proposed method can be used efficiently.
基金Supported by the Educational Commission of Hubei Province of China(Grant No.D20112503)National Natural Science Foundation of China(Grant No.11071022)
文摘With the upper bound of Kullback-Leibler distance between a matrix variate Beta-distri- bution and a normal distribution, this paper gives the conditions under which a matrix-variate Beta- distribution will approach uniformly and asymptotically a normal distribution.
基金This research was funded by the National Natural Science Foundation of China under Grants 62271202,62027802,and 61831008the Key Research and Development Program of Zhejiang Province under Grant 2023C01003in part by the Open Foundation of State Key Laboratory of Integrated Services Networks Xidian University under Grant ISN23-01.
文摘We analyzed the performance of a freespace optical(FSO)system in this study,considering the combined effects of atmospheric turbulence,fog absorption,and pointing errors.The impacts of atmospheric turbulence and foggy absorption were modeled using the Fisher-Snedecor F distribution and the Gamma distribution,respectively.Next,we derived the probability density function(PDF)and cumulative probability density function of the optical system under these combined effects.Based on these statistical findings,closed-form expressions for various system metrics,such as outage probability,average bit error rate(BER),and ergodic capacity,were derived.Furthermore,we used a deep neural network(DNN)to predict the ergodic capacity of the system,achieving reduced running time and improved accuracy.Finally,the accuracy of the prediction results was validated by comparing them with the analytical results.
