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
The network structures of smart substations and the characteristics of industrial Ethernet switches are analyzed.The testing technologies of network systems based on smart substations are specifically elaborated.A vie...The network structures of smart substations and the characteristics of industrial Ethernet switches are analyzed.The testing technologies of network systems based on smart substations are specifically elaborated.A viewpoint is proposed that special testing policy&method of smart substation networks should be followed,so that the results can reveal the real network data exchange performance of the whole station.This view ensures the safety and stability of smart substations and lays a foundation for future upgrades and expansions.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The network structures of smart substations and the characteristics of industrial Ethernet switches are analyzed.The testing technologies of network systems based on smart substations are specifically elaborated.A viewpoint is proposed that special testing policy&method of smart substation networks should be followed,so that the results can reveal the real network data exchange performance of the whole station.This view ensures the safety and stability of smart substations and lays a foundation for future upgrades and expansions.
