Phosphorus boosts lithium-ion battery charge capacity

Fayalite (α-Fe2SiO4) with an orthorhombic crystalline structure delivers an initial discharge/charge capacity of 849.0 mA h g−1/514.5 mA h g−1 and a second discharge/charge capacity of 504.9 mA h g−1/489.5 mA h g−1 at a current rate of 0.1 C.

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An optimal wireless power transfer system for Lithium-ion battery charge

2016 IEEE 6th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) ◽

10.1109/icce-berlin.2016.7684717 ◽

2016 ◽

Cited By ~ 1

Author(s):

Yuto Honda ◽

Lei Lin ◽

Masahiro Fukui

Keyword(s):

Lithium Ion Battery ◽

Lithium Ion ◽

Wireless Power Transfer ◽

Transfer System ◽

Power Transfer ◽

Wireless Power ◽

Battery Charge ◽

Wireless Power Transfer System

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Nonlinear Mixed Effect Model-Based Prognostics for Lithium-ion Battery Charge Decay

2018 Annual Reliability and Maintainability Symposium (RAMS) ◽

10.1109/ram.2018.8463128 ◽

2018 ◽

Author(s):

Chinedu I. Ossai ◽

Nagarajan Raghavan

Keyword(s):

Lithium Ion Battery ◽

Lithium Ion ◽

Mixed Effect Model ◽

Mixed Effect ◽

Battery Charge ◽

Model Based ◽

Nonlinear Mixed Effect Model ◽

Nonlinear Mixed Effect ◽

Effect Model ◽

Charge Decay

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A Battery SOC Estimation Method Based on AFFRLS-EKF

Sensors ◽

10.3390/s21175698 ◽

2021 ◽

Vol 21 (17) ◽

pp. 5698

Author(s):

Ming Li ◽

Yingjie Zhang ◽

Zuolei Hu ◽

Ying Zhang ◽

Jing Zhang

Keyword(s):

Least Squares ◽

Lithium Ion Battery ◽

Estimation Method ◽

Lithium Ion ◽

Recursive Least Squares ◽

Estimation Accuracy ◽

Forgetting Factor ◽

Battery Charge ◽

Estimation Strategy ◽

Soc Estimation

The lithium-ion battery is the key power source of a hybrid vehicle. Accurate real-time state of charge (SOC) acquisition is the basis of the safe operation of vehicles. In actual conditions, the lithium-ion battery is a complex dynamic system, and it is tough to model it accurately, which leads to the estimation deviation of the battery SOC. Recursive least squares (RLS) algorithm with fixed forgetting factor is widely used in parameter identification, but it lacks sufficient robustness and accuracy when battery charge and discharge conditions change suddenly. In this paper, we proposed an adaptive forgetting factor regression least-squares–extended Kalman filter (AFFRLS–EKF) SOC estimation strategy by designing the forgetting factor of least squares algorithm to improve the accuracy of SOC estimation under the change of battery charge and discharge conditions. The simulation results show that the SOC estimation strategy of the AFFRLS–EKF based on accurate modeling can effectively improve the estimation accuracy of SOC.

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Effects of Alumina Films on N-Doped Carbon Nanotubes/Graphene Composites as Anode Materials of Lithium-Ion Batteries

Journal of Nanomaterials ◽

10.1155/2020/6690401 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Chuen-Chang Lin ◽

Shu-Pei Hsu ◽

Guang-Jhong Chen

Keyword(s):

Carbon Nanotubes ◽

Lithium Ion Battery ◽

Coulombic Efficiency ◽

Lithium Ion ◽

Electrochemical Stability ◽

Discharge Process ◽

Charge Capacity ◽

Graphene Composite ◽

Coin Cell ◽

Initial Coulombic Efficiency

A carbon nanotubes/graphene composite is grown on nickel foil without additional catalysts by one-step ambient pressure chemical vapor deposition (CVD). Next, the carbon nanotubes/graphene composite is modified by radio frequency (RF) nitrogen plasma. Finally, to improve its initial coulombic efficiency/electrochemical stability, lower potential during the charge process (coin cell), and boost potential during the discharge process (lithium-ion battery), alumina is deposited onto the N-doped carbon nanotubes/graphene composite by RF magnetron sputtering at different power levels and periods of time. The charge specific capacity (597 mAh/g) and initial coulombic efficiency (81.44% > 75.02% for N-doped carbon nanotubes/graphene) of Al2O3/N-doped CNTs/graphene for the coin cell reached a maximum at the best sputtering condition ( power = 65 W and time = 30 min ). Al2O3/N-doped CNTs/graphene (the best sputtering condition) exhibits higher initial coulombic efficiency (79.8%) compared with N-doped CNTs/graphene (initial coulombic efficiency: 74.3%) for the lithium-ion battery. Furthermore, the achievement fraction (about 70%) of full charge capacity (coin cell) for Al2O3/N-doped carbon nanotubes/graphene (the best sputtering condition) is higher than that (about 30%) for N-doped carbon nanotubes/graphene at a voltage lower than about 0.25 V. Moreover, it also shows a little higher electrochemical stability (coin cell) of charge capacity for Al2O3/N-doped carbon nanotubes/graphene (the best sputtering condition) in comparison with N-doped carbon nanotubes/graphene and Al2O3/N-doped CNTs/graphene (the best sputtering condition) exhibits better cyclic stability (lithium-ion battery) of discharge capacity compared with N-doped CNTs/graphene.

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