Results 21 to 30 of about 721,726 (209)

Stable and Accurate Estimation of SOC Using eXogenous Kalman Filter for Lithium-Ion Batteries

Sensors, 2023
The state of charge (SOC) for a lithium-ion battery is a key index closely related to battery performance and safety with respect to the power supply system of electric vehicles.
Qizhe Lin, Xiaoqi Li, Bicheng Tu, Junwei Cao, Ming Zhang, Jiawei Xiang   +5 more
doaj   +1 more source

Low Temperature, Current Dependent Battery State Estimation Using Interacting Multiple Model Strategy

IEEE Access, 2021
Lithium-ion battery State of Charge (SoC) estimation for Electric Vehicle (EV) applications must be robust and as accurate as possible to maximize battery utilization and ensure safe operation over a wide range of operating conditions.
Marvin Messing, Sara Rahimifard, Tina Shoa, Saeid Habibi   +3 more
doaj   +1 more source

Lithium-ion battery state-of-charge estimation based on a dual extended Kalman filter and BPNN correction

Connection Science, 2022
It is challenging for a battery management system to estimate the State-Of-Charge (SOC) of batteries. A novel model-based method, using a Dual Extended Kalman Filtering algorithm (DEKF) and Back Propagation Neural Network (BPNN), is proposed to estimate ...
Likun Xing, Liuyi Ling, Xianyuan Wu
doaj   +1 more source

Comparative Study of the Influence of Open Circuit Voltage Tests on State of Charge Online Estimation for Lithium-Ion Batteries

IEEE Access, 2020
The accurate state of charge (SoC) online estimation is a significant indicator that relates to driving ranges of electric vehicles (EV). The relationship between open circuit voltage (OCV) and SoC plays an important role in SoC estimation for lithium ...
Yuan Li, Hao Guo, Fei Qi, Zhiping Guo, Meiying Li   +4 more
doaj   +1 more source

Estimation of the SOC of Energy-Storage Lithium Batteries Based on the Voltage Increment

IEEE Access, 2020
State of charge (SOC) estimations are an important part of lithium-ion battery management systems. Aiming at existing SOC estimation algorithms based on neural networks, the voltage increment is proposed in this paper as a new input feature for ...
Bo Zhao, Juan Hu, Shouping Xu, Jiangzhao Wang, Yanqing Zhu, Li Zhang, Chaofei Gao   +6 more
doaj   +1 more source

Open-Circuit Voltage Models for Battery Management Systems: A Review

Energies, 2022
A battery management system (BMS) plays a crucial role to ensure the safety, efficiency, and reliability of a rechargeable Li-ion battery pack. State of charge (SOC) estimation is an important operation within a BMS.
Prarthana Pillai, Sneha Sundaresan, Pradeep Kumar, Krishna R. Pattipati, Balakumar Balasingam   +4 more
doaj   +1 more source

Maximum-likelihood estimation for diffusion processes via closed-form density expansions [PDF]

, 2013
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data.
Li, Chenxu
core   +1 more source

New battery model and state-of-health determination through subspace parameter estimation and state-observer techniques [PDF]

, 2009
This paper describes a novel adaptive battery model based on a remapped variant of the well-known Randles' lead-acid model. Remapping of the model is shown to allow improved modeling capabilities and accurate estimates of dynamic circuit parameters when ...
Bentley, P., Bingham, C.M., Gould, C.R., Stone, D.A.   +3 more
core   +2 more sources

Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries

Energies, 2018
State of charge (SOC) is one of the most important parameters in battery management systems, as it indicates the available battery capacity at every moment.
Ana-Irina Stroe, Jinhao Meng, Daniel-Ioan Stroe, Maciej Świerczyński, Remus Teodorescu, Søren Knudsen Kær   +5 more
doaj   +1 more source

Quantum Algorithms Revisited [PDF]

, 1997
Quantum computers use the quantum interference of different computational paths to enhance correct outcomes and suppress erroneous outcomes of computations.
Cleve, Richard, Ekert, Artur, Macchiavello, Chiara, Mosca, Michele   +3 more
core   +5 more sources