Lithium-ion batteries are the most widely used energy storage devices,for which the accurate prediction of the remaining useful life(RUL)is crucial to their reliable operation and accident prevention.This work thoroug...Lithium-ion batteries are the most widely used energy storage devices,for which the accurate prediction of the remaining useful life(RUL)is crucial to their reliable operation and accident prevention.This work thoroughly investigates the developmental trend of RUL prediction with machine learning(ML)algorithms based on the objective screening and statistics of related papers over the past decade to analyze the research core and find future improvement directions.The possibility of extending lithium-ion battery lifetime using RUL prediction results is also explored in this paper.The ten most used ML algorithms for RUL prediction are first identified in 380 relevant papers.Then the general flow of RUL prediction and an in-depth introduction to the four most used signal pre-processing techniques in RUL prediction are presented.The research core of common ML algorithms is given first time in a uniform format in chronological order.The algorithms are also compared from aspects of accuracy and characteristics comprehensively,and the novel and general improvement directions or opportunities including improvement in early prediction,local regeneration modeling,physical information fusion,generalized transfer learning,and hardware implementation are further outlooked.Finally,the methods of battery lifetime extension are summarized,and the feasibility of using RUL as an indicator for extending battery lifetime is outlooked.Battery lifetime can be extended by optimizing the charging profile serval times according to the accurate RUL prediction results online in the future.This paper aims to give inspiration to the future improvement of ML algorithms in battery RUL prediction and lifetime extension strategy.展开更多
Wireless Sensor Networks(WSNs)have hardware and software limitations and are deployed in hostile environments.The problem of energy consumption in WSNs has become a very important axis of research.To obtain good perfo...Wireless Sensor Networks(WSNs)have hardware and software limitations and are deployed in hostile environments.The problem of energy consumption in WSNs has become a very important axis of research.To obtain good performance in terms of the network lifetime,several routing protocols have been proposed in the literature.Hierarchical routing is considered to be the most favorable approach in terms of energy efficiency.It is based on the concept parent-child hierarchy where the child nodes forward their messages to their parent,and then the parent node forwards them,directly or via other parent nodes,to the base station(sink).In this paper,we present a new Energy-Efficient clustering protocol for WSNs using an Objective Function and Random Search with Jumps(EEOFRSJ)in order to reduce sensor energy consumption.First,the objective function is used to find an optimal cluster formation taking into account the ratio of the mean Euclidean distance of the nodes to their associated cluster heads(CH)and their residual energy.Then,we find the best path to transmit data from the CHs nodes to the base station(BS)using a random search with jumps.We simulated our proposed approach compared with the Energy-Efficient in WSNs using Fuzzy C-Means clustering(EEFCM)protocol using Matlab Simulink.Simulation results have shown that our proposed protocol excels regarding energy consumption,resulting in network lifetime extension.展开更多
Overall purpose of a power uprate and lifetime extension project （PLEX） is to modernize the power station cost-efficiently resulting in fulfilling the following overall requirements. The primary target is to meet th...Overall purpose of a power uprate and lifetime extension project （PLEX） is to modernize the power station cost-efficiently resulting in fulfilling the following overall requirements. The primary target is to meet the requirements provided by the local regulations from the regulatory offices. The controlling, monitoring and power supply of safety functions have to comply with these regulations. Any deviations from the existing safety analysis report （SAR） have to be corrected. On top of the safety measures the general technical status should be raised to extend the lifetime to 60 years. A high availability during the modernization has to be assured.展开更多
One of the most important issues of wireless sensor networks is how to transfer information from the network nodes to a base station and choose the best possible path for this purpose. Choosing the best path can be ba...One of the most important issues of wireless sensor networks is how to transfer information from the network nodes to a base station and choose the best possible path for this purpose. Choosing the best path can be based on different factors such as energy consumption, response time, delay, and data transfer accuracy. Increasing the network lifetime is the most challenging problem. One of the latest energy-aware routing methods is to use the harmony search algorithm in the small-scale sensor networks. The aim of this study is to introduce the harmony search algorithm as a successful metaheuristic algorithm for wireless sensor network routing in order to increase the lifetime of such networks. This study is intended to improve the objective function for energy efficiency in the harmony search algorithm to establish balance between the network energy consumption and path length control. Therefore, it is necessary to choose the initial energy of each node randomly from a certain range as the path energy consumption should be low to choose a path which can consider the residual energy. In other words, a path should be chosen to establish balance between the network energy consumption and the minimum residual energy. The simulation results indicate that the proposed objective function provides a longer lifetime by 26.12% compared with EEHSBR.展开更多
基金funded by China Scholarship Council,The fund numbers are 202108320111,202208320055。
文摘Lithium-ion batteries are the most widely used energy storage devices,for which the accurate prediction of the remaining useful life(RUL)is crucial to their reliable operation and accident prevention.This work thoroughly investigates the developmental trend of RUL prediction with machine learning(ML)algorithms based on the objective screening and statistics of related papers over the past decade to analyze the research core and find future improvement directions.The possibility of extending lithium-ion battery lifetime using RUL prediction results is also explored in this paper.The ten most used ML algorithms for RUL prediction are first identified in 380 relevant papers.Then the general flow of RUL prediction and an in-depth introduction to the four most used signal pre-processing techniques in RUL prediction are presented.The research core of common ML algorithms is given first time in a uniform format in chronological order.The algorithms are also compared from aspects of accuracy and characteristics comprehensively,and the novel and general improvement directions or opportunities including improvement in early prediction,local regeneration modeling,physical information fusion,generalized transfer learning,and hardware implementation are further outlooked.Finally,the methods of battery lifetime extension are summarized,and the feasibility of using RUL as an indicator for extending battery lifetime is outlooked.Battery lifetime can be extended by optimizing the charging profile serval times according to the accurate RUL prediction results online in the future.This paper aims to give inspiration to the future improvement of ML algorithms in battery RUL prediction and lifetime extension strategy.
文摘Wireless Sensor Networks(WSNs)have hardware and software limitations and are deployed in hostile environments.The problem of energy consumption in WSNs has become a very important axis of research.To obtain good performance in terms of the network lifetime,several routing protocols have been proposed in the literature.Hierarchical routing is considered to be the most favorable approach in terms of energy efficiency.It is based on the concept parent-child hierarchy where the child nodes forward their messages to their parent,and then the parent node forwards them,directly or via other parent nodes,to the base station(sink).In this paper,we present a new Energy-Efficient clustering protocol for WSNs using an Objective Function and Random Search with Jumps(EEOFRSJ)in order to reduce sensor energy consumption.First,the objective function is used to find an optimal cluster formation taking into account the ratio of the mean Euclidean distance of the nodes to their associated cluster heads(CH)and their residual energy.Then,we find the best path to transmit data from the CHs nodes to the base station(BS)using a random search with jumps.We simulated our proposed approach compared with the Energy-Efficient in WSNs using Fuzzy C-Means clustering(EEFCM)protocol using Matlab Simulink.Simulation results have shown that our proposed protocol excels regarding energy consumption,resulting in network lifetime extension.
文摘Overall purpose of a power uprate and lifetime extension project （PLEX） is to modernize the power station cost-efficiently resulting in fulfilling the following overall requirements. The primary target is to meet the requirements provided by the local regulations from the regulatory offices. The controlling, monitoring and power supply of safety functions have to comply with these regulations. Any deviations from the existing safety analysis report （SAR） have to be corrected. On top of the safety measures the general technical status should be raised to extend the lifetime to 60 years. A high availability during the modernization has to be assured.
文摘One of the most important issues of wireless sensor networks is how to transfer information from the network nodes to a base station and choose the best possible path for this purpose. Choosing the best path can be based on different factors such as energy consumption, response time, delay, and data transfer accuracy. Increasing the network lifetime is the most challenging problem. One of the latest energy-aware routing methods is to use the harmony search algorithm in the small-scale sensor networks. The aim of this study is to introduce the harmony search algorithm as a successful metaheuristic algorithm for wireless sensor network routing in order to increase the lifetime of such networks. This study is intended to improve the objective function for energy efficiency in the harmony search algorithm to establish balance between the network energy consumption and path length control. Therefore, it is necessary to choose the initial energy of each node randomly from a certain range as the path energy consumption should be low to choose a path which can consider the residual energy. In other words, a path should be chosen to establish balance between the network energy consumption and the minimum residual energy. The simulation results indicate that the proposed objective function provides a longer lifetime by 26.12% compared with EEHSBR.
