Languang Lu

Electrical and Electronic Engineering · 2013–2021

A researcher in the Science corpus: 36 papers; trusts 33 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

Whom Languang Lu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Xuning Feng
  2. Minggao Ouyang
  3. Matthieu Dubarry
  4. R. Spotnitz
  5. Xiaosong Hu
  6. Xuebing Han
  7. Qingsong Wang
  8. Fredrik Larsson
  9. Dongsheng Ren
  10. P. Ramadass

Who trusts Languang Lu overall

  1. Xuning Feng
  2. Xiaosong Hu
  3. Minggao Ouyang
  4. Kailong Liu
  5. Dongsheng Ren
  6. Prashant Shrivastava
  7. Rui Xiong
  8. M. R. Palacín
  9. Xuebing Han
  10. Kirti Richa

Papers from Languang Lu's perspective

Ordered by how strongly the researchers Languang Lu trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling (IEEE transactions on industrial electronics (1982. Print))
  2. State-of-health monitoring of lithium-ion battery modules and packs via incremental capacity peak tracking
  3. A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors (Journal of Power Sources)
  4. Effects of overdischarge on performance and thermal stability of a Li-ion cell
  5. A General Discussion of Li Ion Battery Safety
  6. Experimental and modeling analysis of thermal runaway propagation over the large format energy storage battery module with Li4Ti5O12 anode
  7. State of Charge and State of Health Estimation for Lithium Batteries Using Recurrent Neural Networks (IEEE Transactions on Vehicular Technology)
  8. Co-Estimation of State of Charge and State of Health for Lithium-Ion Batteries Based on Fractional-Order Calculus (IEEE Transactions on Vehicular Technology)
  9. Lithium-Ion Battery Health Prognosis Based on a Real Battery Management System Used in Electric Vehicles (IEEE Transactions on Vehicular Technology)
  10. Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries (IEEE Transactions on Vehicular Technology)

Their papers