Battery state-of-charge estimation methods

[1]  Sheng Liu,et al.  Reduced-Coupling Coestimation of SOC and SOH for Lithium-Ion Batteries Based on Convex Optimization , 2020, IEEE Transactions on Power Electronics.

[2]  Xuezhe Wei,et al.  An online SOC and capacity estimation method for aged lithium-ion battery pack considering cell inconsistency , 2020 .

[3]  Jianlong Qiu,et al.  A GRU-RNN based momentum optimized algorithm for SOC estimation , 2020 .

[4]  Ruixin Yang,et al.  A novel approach to reconstruct open circuit voltage for state of charge estimation of lithium ion batteries in electric vehicles , 2019 .

[5]  Yujie Wang,et al.  A framework for state-of-charge and remaining discharge time prediction using unscented particle filter , 2020 .

[6]  P. Hurley,et al.  Emulating synaptic response in n- and p-channel MoS2 transistors by utilizing charge trapping dynamics , 2020, Scientific Reports.

[7]  Daniel-Ioan Stroe,et al.  A novel energy management strategy for the ternary lithium batteries based on the dynamic equivalent circuit modeling and differential Kalman filtering under time-varying conditions , 2020, Journal of Power Sources.

[8]  Chunyun Fu,et al.  State of charge estimation for lithium-ion batteries based on adaptive dual Kalman filter , 2020, Applied Mathematical Modelling.

[9]  Hicham Chaoui,et al.  An Adaptive State Machine Based Energy Management Strategy for a Multi-Stack Fuel Cell Hybrid Electric Vehicle , 2020, IEEE Transactions on Vehicular Technology.

[10]  Zhang Xiaoqin,et al.  A novel endurance prediction method of series connected lithium-ion batteries based on the voltage change rate and iterative calculation , 2019, Journal of Cleaner Production.

[11]  Daniel-Ioan Stroe,et al.  Sizing Study of Second Life Li-ion Batteries for Enhancing Renewable Energy Grid Integration , 2016, IEEE Transactions on Industry Applications.

[12]  Zhanfeng Li,et al.  An integrated online adaptive state of charge estimation approach of high-power lithium-ion battery packs , 2018, Trans. Inst. Meas. Control.

[13]  Guang Li,et al.  An adaptive fusion estimation algorithm for state of charge of lithium-ion batteries considering wide operating temperature and degradation , 2020 .

[14]  Hui Shen,et al.  Secure Communication Scheme Based on a New 5D Multistable Four-Wing Memristive Hyperchaotic System with Disturbance Inputs , 2020, Complex..

[15]  Zhanfeng Li,et al.  Online state of charge estimation for the aerial lithium-ion battery packs based on the improved extended Kalman filter method , 2017 .

[16]  Jian-hang Zhang,et al.  Real-time peak power prediction for zinc nickel single flow batteries , 2020, Journal of Power Sources.

[17]  Nicolae Tudoroiu,et al.  Real Time Design and Implementation of State of Charge Estimators for a Rechargeable Lithium-Ion Cobalt Battery with Applicability in HEVs/EVs—A Comparative Study , 2020 .

[18]  Jie Su,et al.  The parameter identification method study of the splice equivalent circuit model for the aerial lithium-ion battery pack , 2018 .

[19]  Shun-Li Wang,et al.  Adaptive State-of-Charge Estimation Method for an Aeronautical Lithium-ion Battery Pack Based on a Reduced Particle-unscented Kalman Filter , 2018 .

[20]  Feng He,et al.  A Method to Identify Lithium Battery Parameters and Estimate SOC Based on Different Temperatures and Driving Conditions , 2019 .

[21]  Meng Li,et al.  Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries , 2020 .

[22]  Hao Wang,et al.  An Energy Balanced and Lifetime Extended Routing Protocol for Underwater Sensor Networks , 2018, Sensors.

[23]  Neil Hewitt,et al.  Design, Valuation and Comparison of Demand Response Strategies for Congestion Management , 2020 .

[24]  Chenghui Zhang,et al.  A low-complexity state of charge estimation method for series-connected lithium-ion battery pack used in electric vehicles , 2019, Journal of Power Sources.

[25]  Xiaojiao Chen,et al.  Hybrid extended-unscented Kalman filters for continuous-time nonlinear fractional-order systems involving process and measurement noises , 2020, Trans. Inst. Meas. Control.

[26]  Dheerendra Singh,et al.  Hardware-in-the-loop Implementation of ANFIS based Adaptive SoC Estimation of Lithium-ion Battery for Hybrid Vehicle Applications , 2020 .

[27]  Yan Yang,et al.  The multi-innovation extended Kalman filter algorithm for battery SOC estimation , 2020, Ionics.

[28]  Suli Wang,et al.  Hybrid Polymer Nanoarrays with Bifunctional Conductance of Ions and Electrons and Enhanced Electrochemical Interfaces. , 2017, ACS applied materials & interfaces.

[29]  Pedro Rodriguez,et al.  Technical Viability of Battery Second Life: A Study From the Ageing Perspective , 2018, IEEE Transactions on Industry Applications.

[30]  Fei Xie,et al.  A Novel Battery State of Charge Estimation Based on the Joint Unscented Kalman Filter and Support Vector Machine Algorithms , 2020 .

[31]  Daniel-Ioan Stroe,et al.  A novel power state evaluation method for the lithium battery packs based on the improved external measurable parameter coupling model , 2020 .

[32]  Peng Wang,et al.  State of Charge Estimation of Lithium Battery Based on Improved Correntropy Extended Kalman Filter , 2020 .

[33]  Remus Teodorescu,et al.  Lifetime Estimation of the Nanophosphate $\hbox{LiFePO}_{4}\hbox{/C}$ Battery Chemistry Used in Fully Electric Vehicles , 2015, IEEE Transactions on Industry Applications.

[34]  Weiqun Liu,et al.  A state of charge estimation method for lithium-ion batteries based on fractional order adaptive extended kalman filter , 2019, Energy.

[35]  Guangdi Hu,et al.  State of charge estimation in electric vehicles at various ambient temperatures , 2020, International Journal of Energy Research.

[36]  Kai Wang,et al.  Online State of Charge Estimation of Lithium-Ion Cells Using Particle Filter-Based Hybrid Filtering Approach , 2020, Complex..

[37]  Cong Yan,et al.  Lithium-Ion Battery Parameters and State of Charge Joint Estimation Using Bias Compensation Least Squares and the Alternate Algorithm , 2020 .

[38]  Chao Jiang,et al.  Robust Remaining Useful Life Estimation Based on an Improved Unscented Kalman Filtering Method , 2020 .

[39]  Chuan-Yun Zou,et al.  An improved packing equivalent circuit modeling method with the cell‐to‐cell consistency state evaluation of the internal connected lithium‐ion batteries , 2019, Energy Science & Engineering.

[40]  Yujie Wang,et al.  Model migration based battery power capability evaluation considering uncertainties of temperature and aging , 2019, Journal of Power Sources.

[41]  Wei Qi,et al.  New SOC estimation method under multi-temperature conditions based on parametric-estimation OCV , 2020, Journal of Power Electronics.

[42]  Jianbo Ji,et al.  A novel model-based state of charge estimation for lithium-ion battery using adaptive robust iterative cubature Kalman filter , 2019 .

[43]  Gregory L. Plett,et al.  Postprocessing the outputs of an interacting multiple-model Kalman filter using a Markovian trellis to estimate parameter values of aged Li-ion cells , 2020 .

[44]  Ruixin Yang,et al.  A set membership theory based parameter and state of charge co-estimation method for all-climate batteries , 2020 .

[45]  Xiong Xin.  A Novel State of Charge Estimation Method for Ternary Lithium Batteries Based on System Function and Extended Kalman Filter , 2020 .

[46]  Lin Hu,et al.  Active cell balancing of lithium‐ion battery pack based on average state of charge , 2020, International Journal of Energy Research.

[47]  Qi Zhang,et al.  Remaining useful life prediction of lithium‐ion battery based on extended Kalman particle filter , 2019, International Journal of Energy Research.

[48]  Shun-Li Wang,et al.  Open circuit voltage and state of charge relationship functional optimization for the working state monitoring of the aerial lithium-ion battery pack , 2018, Journal of Cleaner Production.

[49]  Wenhua Xu,et al.  Novel reduced-order modeling method combined with three-particle nonlinear transform unscented Kalman filtering for the battery state-of-charge estimation , 2020, Journal of Power Electronics.

[50]  Joint Estimation of Ternary Lithium-ion Battery State of Charge and State of Power Based on Dual Polarization Model , 2020 .

[51]  Jianguo Liu,et al.  Analyses and optimization of electrolyte concentration on the electrochemical performance of iron-chromium flow battery , 2020 .

[52]  Shun-Li Wang,et al.  A novel weight coefficient calculation method for the real‐time state monitoring of the lithium‐ion battery packs under the complex current variation working conditions , 2019, Energy Science & Engineering.

[53]  Zheshu Ma,et al.  LPV Estimation of SOC Based on Electricity Conversion and Hysteresis Characteristic , 2019 .

[54]  Long Zhou,et al.  A hybrid state-of-charge estimation method based on credible increment for electric vehicle applications with large sensor and model errors , 2020 .

[55]  Xu Guo,et al.  A data-driven coulomb counting method for state of charge calibration and estimation of lithium-ion battery , 2020 .

[56]  Guangzhong Dong,et al.  Data-Driven Battery Health Prognosis Using Adaptive Brownian Motion Model , 2020, IEEE Transactions on Industrial Informatics.

[57]  Jose-Maria Molina-Garcia-Pardo,et al.  Contribution to the Channel Path Loss and Time-Dispersion Characterization in an Office Environment at 26 GHz , 2019 .

[58]  Giovanni Lutzemberger,et al.  Luenberger-based State-Of-Charge evaluation and experimental validation with lithium cells , 2020 .

[59]  Wei Xu,et al.  Lithium-ion battery state of charge and parameters joint estimation using cubature Kalman filter and particle filter , 2019, Journal of Power Electronics.

[60]  Hafedh Trabelsi,et al.  An online state of charge estimation for Lithium-ion and supercapacitor in hybrid electric drive vehicle , 2019 .

[61]  W. Xu,et al.  A multi‐timescale adaptive dual particle filter for state of charge estimation of lithium‐ion batteries considering temperature effect , 2020, Energy Science & Engineering.

[62]  Ming Liu,et al.  Estimation for state-of-charge of lithium-ion battery based on an adaptive high-degree cubature Kalman filter , 2019 .

[63]  Aini Hussain,et al.  Toward Enhanced State of Charge Estimation of Lithium-ion Batteries Using Optimized Machine Learning Techniques , 2020, Scientific Reports.

[64]  Jie Su,et al.  An equivalent circuit model analysis for the lithium-ion battery pack in pure electric vehicles , 2019, Measurement and Control.

[65]  X. Fang,et al.  Freeze-drying induced self-assembly approach for scalable constructing MoS2/graphene hybrid aerogels for lithium-ion batteries. , 2019, Journal of colloid and interface science.

[66]  Zhang Li,et al.  A comprehensive working state monitoring method for power battery packs considering state of balance and aging correction , 2019, Energy.

[67]  Li Kai,et al.  Battery life estimation based on cloud data for electric vehicles , 2020 .

[68]  Jing Sun,et al.  The Sequential Algorithm for Combined State of Charge and State of Health Estimation of Lithium Ion Battery based on Active Current Injection , 2019, Energy.

[69]  Hao Wang,et al.  Fuzzy logic vector–based forwarding routing protocol for underwater acoustic sensor networks , 2018, Trans. Emerg. Telecommun. Technol..

[70]  Chuan-Yun Zou,et al.  A novel practical state of charge estimation method: an adaptive improved ampere‐hour method based on composite correction factor , 2020, International Journal of Energy Research.

[71]  Bin Li,et al.  Battery states online estimation based on exponential decay particle swarm optimization and proportional-integral observer with a hybrid battery model , 2020 .

[72]  Shun-Li Wang,et al.  An adaptive working state iterative calculation method of the power battery by using the improved Kalman filtering algorithm and considering the relaxation effect , 2019, Journal of Power Sources.

[73]  Juan-Carlos Cano,et al.  A Location-Aware Waypoint-Based Routing Protocol for Airborne DTNs in Search and Rescue Scenarios , 2018, Sensors.

[74]  Yuehua Cheng,et al.  Dynamic Long Short-Term Memory Neural-Network- Based Indirect Remaining-Useful-Life Prognosis for Satellite Lithium-Ion Battery , 2018, Applied Sciences.

[75]  Y. Chu,et al.  H-Coverings of Path-Amalgamated Ladders and Fans , 2020, Mathematical Problems in Engineering.

[76]  Cheng Zhang,et al.  State of charge estimation for lithium‐ion battery based on an intelligent adaptive unscented Kalman filter , 2020, International Journal of Energy Research.

[77]  Jian-hua Cheng,et al.  A State of Charge Estimation Method of Lithium-Ion Battery Based on Fused Open Circuit Voltage Curve , 2020, Applied Sciences.

[78]  Lu Wang,et al.  A novel safety anticipation estimation method for the aerial lithium-ion battery pack based on the real-time detection and filtering , 2018, Journal of Cleaner Production.

[79]  Daniel-Ioan Stroe,et al.  A novel charged state prediction method of the lithium ion battery packs based on the composite equivalent modeling and improved splice Kalman filtering algorithm , 2020, Journal of Power Sources.