Standout Papers

Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis 2024 2026169
  1. Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis (2024)
    Fujin Wang, Zhi Zhai et al. Nature Communications

Immediate Impact

21 standout
Sub-graph 1 of 11

Citing Papers

A review on physics-informed data-driven remaining useful life prediction: Challenges and opportunities
2024 Standout
State of Health (SoH) estimation methods for second life lithium-ion battery—Review and challenges
2024 Standout
2 intermediate papers

Works of Fujin Wang being referenced

Explainability-driven model improvement for SOH estimation of lithium-ion battery
2022
A transferable lithium-ion battery remaining useful life prediction method from cycle-consistency of degradation trend
2022

Author Peers

Author Last Decade Papers Cites
Fujin Wang 342 274 140 12 414
Darius Roman 385 360 98 8 482
Ashish Khandelwal 348 365 108 12 442
Kun Zhao 365 349 130 14 510
Jiantao Qu 272 253 82 14 459
Muhammad Junaid Alvi 282 327 72 13 440
Zijian Zhang 308 268 87 10 384
Zhelin Huang 232 215 144 10 417
Xiang Li 446 414 94 13 494
Shunkun Yang 313 304 88 19 464
Xiujuan Zheng 336 282 196 23 489

All Works

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Rankless by CCL
2026