Xuning Feng

Electrical and Electronic Engineering · 2013–2021

A researcher in the Science corpus: 37 papers; trusts 33 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Xuning Feng trusts overall

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

  1. Minggao Ouyang
  2. Languang Lu
  3. R. Spotnitz
  4. Xuebing Han
  5. Qingsong Wang
  6. Xiangming He
  7. Dongsheng Ren
  8. Shriram Santhanagopalan
  9. Xiaosong Hu
  10. Fredrik Larsson

Who trusts Xuning Feng overall

  1. Dongsheng Ren
  2. Xiaosong Hu
  3. Minggao Ouyang
  4. Languang Lu
  5. Xiangming He
  6. Ping Ping
  7. Peifeng Huang
  8. Kailong Liu
  9. Qingsong Wang
  10. Xianke Lin

Papers from Xuning Feng's perspective

Ordered by how strongly the researchers Xuning Feng 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. A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors (Journal of Power Sources)
  3. State-of-health monitoring of lithium-ion battery modules and packs via incremental capacity peak tracking
  4. Experimental and modeling analysis of thermal runaway propagation over the large format energy storage battery module with Li4Ti5O12 anode
  5. Thermal behaviour analysis of lithium-ion battery at elevated temperature using deconvolution method
  6. State of Charge and State of Health Estimation for Lithium Batteries Using Recurrent Neural Networks (IEEE Transactions on Vehicular Technology)
  7. Co-Estimation of State of Charge and State of Health for Lithium-Ion Batteries Based on Fractional-Order Calculus (IEEE Transactions on Vehicular Technology)
  8. Lithium-Ion Battery Health Prognosis Based on a Real Battery Management System Used in Electric Vehicles (IEEE Transactions on Vehicular Technology)
  9. Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries (IEEE Transactions on Vehicular Technology)
  10. Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles

Their papers