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References

1 
F. Meng, 2019, Evaluation of the development capability of the new energy vehicle industry: An empirical study from China, Sustainability, Vol. 11, No. 9, pp. 2635DOI
2 
B. Scrosati, 2010, Lithium batteries: Status, prospects and future, J. power sources, Vol. 195, No. 9, pp. 2419-2430DOI
3 
L. Zheng, 2016, Novel methods for estimating lithium-ion battery state of energy and maximum available energy, Applied Energy, Vol. 178, pp. 1-8DOI
4 
R. Zhang, 2018, State of the art of lithium-ion battery SOC estimation for electrical vehicles, Energies, Vol. 11, No. 7, pp. 1820DOI
5 
Z. He, 2020, A method of state-of-charge estimation for EV power lithium-ion battery using a novel adaptive extended Kalman filter, IEEE Trans. Veh. Technol., Vol. 69, No. 12, pp. 14618-14630DOI
6 
S. Zhang, 2020, An improved adaptive unscented kalman filtering for state of charge online estimation of lithium-ion battery, J. energy storage, Vol. 32, pp. 101980DOI
7 
C. Ge, 2022, State of charge estimation of lithium-ion battery based on improved forgetting factor recursive least squares-extended Kalman filter joint algorithm, J. Energy Storage, Vol. 55, pp. 105474DOI
8 
Z. Du, 2021, Data-driven estimation of remaining useful lifetime and state of charge for lithium-ion battery, IEEE Trans. Transp. Electrific., Vol. 8, No. 1, pp. 356-367Google Search
9 
L. Chen, 2023, Joint estimation of state of charge and state of energy of lithium-ion batteries based on optimized bidirectional gated recurrent neural network, IEEE trans. on transportation electrification, Vol. 10, No. 1, pp. 1605-1616Google Search
10 
A. Bavand, 2022, Online estimations of Li-ion battery SOC and SOH applicable to partial charge/discharge, IEEE Trans. on transportation electrification, Vol. 8, No. 3, pp. 3673-3685DOI
11 
H. Xu, 2024, State of Charge Estimation of Lithium-ion Batteries Based on EKF Integrated with PSO-LSTM for Electric Vehicles, IEEE Trans. Transp. Electrific.Google Search
12 
Z. Yu, 2024, Combined EKF–LSTM algorithm-based enhanced state-of-charge estimation for energy storage container cells, J. Power Electronics, Vol. 24, No. 8, pp. 1329-1339DOI
13 
M. Raissi, 2019, Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations, J. Comput. physics, Vol. 378, pp. 686-707DOI
14 
L. Alzubaidi, 2023, A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications, J. Big Data, Vol. 10, No. 1, pp. 46DOI
15 
A. K. Singh, 2023, Hybrid modeling of lithium-ion battery: Physics-informed neural network for battery state estimation, Batteries, Vol. 9, No. 6, pp. 301DOI
16 
P. Aishwarya, I. Cephas, 2024, Physics Informed Neural Networks for Reliable SOC Estimation in Lithium-Ion Battery ManagementGoogle Search
17 
Q. Wang, 2024, Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis, Nat. Commun., Vol. 15, No. 1, pp. 4332DOI
18 
W. Cho, 2023, Hypernetwork-based meta-learning for low-rank physics-informed neural networks, Advances in Neural Information Processing Systems, Vol. 36, pp. 11219-11231DOI
19 
X. Hu, 2012, A comparative study of equivalent circuit models for Li-ion batteries, J. Power Sources, Vol. 198, pp. 359-367DOI
20 
M. Lukic, 2020, Novel parameter identification method for lithium-ion batteries based on curve fittingGoogle Search
21 
W. Cho, 2024, Parameterized physics-informed neural networks for parameterized PDEs, arXiv preprint arXiv: 2408.09446Google Search
22 
Y. Gao, 2022, SVD-PINNs: transfer learning of physics-informed neural networks via singular value decomposition, arXiv preprint arXiv:2205.15582Google Search
23 
M. Dobija, 2024, Accelerating training of physics informed neural network for 1D PDEs with hierarchical matricesGoogle Search
24 
Z. Xiang, 2022, Self-adaptive loss balanced physics-informed neural networks, Neurocomputing, Vol. 496, pp. 11-34DOI
25 
P. Kollmeyer, 2020, LG 18650HG2 Li-ion Battery Data and Example Deep Neural Network xEV SOC Estimator Script, Mendeley Data, Vol. 3Google Search