Carbon fiber-based structural lithium-ion batteries are attracting significant attention in the automotive and aerospace industries due to their dual capability of energy storage and mechanical load-bearing, leading to weight reduction. These batteries utilize lightweight carbon fiber (CF) composites, which offer excellent stiffness, strength-to-weight ratios, and electrical conductivity. Polyacrylonitrile-based CFs, comprising graphitic and amorphous carbon, are particularly suitable for Li-ion battery applications as they allow the storage of lithium ions. However, integrating lithium iron phosphate (LFP) into CFs poses challenges due to complex lab-scale processes and the use of toxic dispersants, hindering large-scale industrial compatibility. To address this, we investigate the development of water-based LFP-integrated CF structural Li-ion batteries. Homogeneous suspensions are created using cellulose nanocrystals (CNCs) to form hybrid structures. The battery system employs LFP-modified CF as the cathode, unsized CF as the anode, and a water-based electrolyte. The LFP-CNC-graphene nanoplatelet (GNP) hybrids are coated onto CFs through immersion coating. Scanning electron microscopy (SEM) images confirm the well-dispersed and well-adhered LFP-CNC-GNP structures on the CF surface, contributing to their mechanical interlocking and electrochemical performance. The batteries demonstrate a specific energy density of 62.67 Wh/kg and a specific capacity of 72.7 mAh/g. Furthermore, the cyclic voltammetry experiments reveal the stability of the LFP-CNC-GNP-coated CF batteries over 200 cycles without degradation. This research enables the engineering of hybrid nanostructured battery laminates using novel LFP-CNC-GNP-coated CFs, opening avenues for the development of innovative Li-ion structural batteries.
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Nonlinear Observer and Simplified Equivalent Circuit Model-based EKF-SOC Estimator of a Rechargeable LiFePo4 cell
The lithium iron phosphate (LFP) battery has more nonlinear characteristic than other battery type. For this reason, when we use electrical equivalent circuit model and the extended Kalman filter (EKF) for estimating the SOC, the estimation performance can be decreased in the nonlinear region. This paper proposes an advance estimation method of state of charge (SOC) for lithium iron phosphate (LFP) batteries. To improve the model accuracy, this paper utilizes the nonlinear observer for identifying the internal parameters of batteries. Furthermore, to reduce the nonlinear effect of the LFP batteries, this paper recast the Kalman process. Therefore, through the proposed method, the performance of SOC estimation can be more accurate and the computational burden is decreased when we apply the embedded system.
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- Award ID(s):
- 1816197
- PAR ID:
- 10109881
- Date Published:
- Journal Name:
- IEEE ICPE 2019 conference in Busan, Korea
- Page Range / eLocation ID:
- 2610-2614
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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