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检索条件"主题词=Particle Filter algorithm"
58 条 记 录,以下是11-20 订阅
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State of Charge Estimation for Electric Vehicle Batteries Based on a particle filter algorithm
State of Charge Estimation for Electric Vehicle Batteries Ba...
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2017 2nd International Conference on Software, Multimedia and Communication Engineering(SMCE 2017)
作者: Jun BI Yong-xing WANG Xiao-mei ZHAO MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology Beijing Jiaotong University Beijing Jiaotong University
Accurate State of Charge(SOC) estimation is critical for improving the battery *** order to realize the accurate estimation of SOC for electric vehicle(EV) batteries,considering the complex operating mode and nonlinea... 详细信息
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Day-ahead PV Power Forecast by Hybrid ANN Compared to the Five Parameters Model Estimated by particle filter algorithm  25th
Day-ahead PV Power Forecast by Hybrid ANN Compared to the Fi...
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25th International Conference on Artificial Neural Networks (ICANN)
作者: Ogliari, Emanuele Bolzoni, Alberto Leva, Sonia Mussetta, Marco Politecn Milan Dept Energy Via Lambruschini 4 I-20156 Milan Italy
A comparison between the hybrid method (PHANN - Physical Hybrid Artificial Neural Network) and the 5 parameter Physical model, which have been determined by the particle filter algorithm, is presented here. These meth... 详细信息
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Iterated Unscented Kalman particle filter algorithm based on a variable-step adaptive artificial fish swarm optimization  35
Iterated Unscented Kalman Particle Filter algorithm based on...
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35th Chinese Control Conference, CCC 2016
作者: Li, Min Chen, Zhimei Shao, Xuejuan School of Electronic and Engineering Taiyuan University of Science and Technology Taiyuan030024 China
Considering the problem of declining in accuracy caused by particles impoverishment in the Iterated Unscented Kalman particle filter algorithm, self-adaptive artificial fish swarm algorithm with changing step optimize... 详细信息
来源: 评论
Iterated Unscented Kalman particle filter algorithm based on a variable-step adaptive Artificial Fish Swarm optimization
Iterated Unscented Kalman Particle Filter algorithm based on...
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第35届中国控制会议
作者: Min LI CHEN Zhimei SHAO Xuejuan School of Electronic and Engineering Taiyuan University of Science & Technology
Considering the problem of declining in accuracy caused by particles impoverishment in the Iterated Unscented Kalman particle filter algorithm,self-adaptive artificial fish swarm algorithm with changing step optimized... 详细信息
来源: 评论
Online identification of battery model parameters and joint state of charge and state of health estimation using dual particle filter algorithms
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INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2022年 第14期46卷 19615-19652页
作者: Xu, Yonghong Chen, Xia Zhang, Hongguang Yang, Fubin Tong, Liang Yang, Yifan Yan, Dong Yang, Anren Yu, Mingzhe Liu, Zhuxian Wang, Yan Beijing Univ Technol Fac Environm & Life Key Lab Enhanced Teat Transfer & Energy Conservat Beijing Key Lab Heat Transfer & Energy Convers Pingleyuan 100 Beijing 100124 Peoples R China Beijing Informat Sci & Technol Univ Sch Elect & Mech Engn Beijing Peoples R China
Aiming at the problems of time-varying battery parameters and inaccurate estimations of state of charge (SOC) and state of health (SOH), a joint estimation algorithm of SOC and SOH is proposed. A particle filter algor... 详细信息
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An improved adaptive weights correction-particle swarm optimization-unscented particle filter method for high-precision online state of charge estimation of lithium-ion batteries
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IONICS 2024年 第1期30卷 311-334页
作者: Li, Zehao Wang, Shunli Yu, Chunmei Qi, Chuangshi Shen, Xianfeng Fernandez, Carlos Southwest Univ Sci & Technol Sch Informat Engn Mianyang 621010 Peoples R China Sichuan Univ Sch Elect Engn Chengdu 610065 Peoples R China Robert Gordon Univ Sch Pharm & Life Sci Aberdeen AB10 7GJ Scotland
In the battery management system (BMS), the state of charge (SOC) of lithium-ion batteries is an indispensable part, and the accuracy of SOC estimation has attracted wide attention. Accurate SOC estimation can improve... 详细信息
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An improved forgetting factor recursive least square and extended particle filtering algorithm for accurate lithium-ion battery state of energy estimation
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IONICS 2024年 第10期30卷 6179-6195页
作者: Shen, Xianfeng Wang, Shunli Yu, Chunmei Li, Zehao Fernandez, Carlos Southwest Univ Sci & Technol Sch Informat Engn Mianyang 621010 Peoples R China Sichuan Univ Sch Elect Engn Chengdu 610065 Peoples R China Robert Gordon Univ Sch Pharm & Life Sci Aberdeen Scotland
State of energy (SOE) estimation of lithium-ion batteries is the basis for electric vehicle range prediction. To improve the estimation accuracy of SOE under complex dynamic operating conditions. In this paper, ternar... 详细信息
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A scale adaptive generative target tracking method based on modified particle filter
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MULTIMEDIA TOOLS AND APPLICATIONS 2023年 第20期82卷 31329-31349页
作者: Xiao, Yuqi Wu, Yongjun Yang, Fan West Anhui Univ Sch Mech & Vehicle Engn Luan City 237012 Anhui Peoples R China Chongqing Jiaotong Univ Sch Traff & Transportat Chongqing 400074 Peoples R China Agr Bank China Zhuzhou Branch Zhuzhou 412000 Hunan Peoples R China
This paper proposes an advanced particle filter (PF) algorithm based on the quantum particle swarm optimization method (QPSO) and adaptive genetic algorithm (QAPF). After resampling of the PF, the position updating eq... 详细信息
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Structural response reconstruction based on the information fusion of multi-source particle filters
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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2023年 第2期37卷 631-641页
作者: Shi, Yonghe Yin, Hong Peng, Zhenrui Wang, Zenghui Bai, Yu Lanzhou Jiaotong Univ Sch Mech Engn Lanzhou 730070 Peoples R China Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Peoples R China
Aiming at the problems that the lack of theoretical basis for the selection of particle set sampling variance and the resampling methods in traditional particle filter algorithms, and sampling process is easily distur... 详细信息
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A novel hybrid information-based PF-WOA algorithm for gas source localization in 3D space
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ROBOTICA 2024年 第11期42卷 3748-3767页
作者: Wang, Li Ren, Ziyu Fan, Shurui Zhang, Yong Hebei Univ Technol Sch Elect Informat Engn Tianjin Peoples R China Tianjin Univ Commerce Sch Informat Engn Tianjin Peoples R China
In recent years, dangerous gas leakage events occur frequently. Rapid and accurate location of gas leakage sources by mobile robots is the key to avoid the expansion of disasters. In order to solve the problem of disc... 详细信息
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