Kailong Liu

Automotive Engineering · 2018–2022

A researcher in the Science corpus: 9 papers; trusts 42 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Automotive Engineering — 285 citations into it
• Electrical and Electronic Engineering — 255 citations into it
• Control and Systems Engineering — 56 citations into it
• Safety, Risk, Reliability and Quality — 35 citations into it

Whom Kailong Liu trusts overall

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

1. Xiaosong Hu
2. Robert R. Richardson
3. Bhaskar Saha
4. S. Y. S. Ng
5. Yinjiao Xing
6. Jingwen Wei
7. Claudio Sbarufatti
8. Xuebing Han
9. Languang Lu
10. Zonghai Chen

Who trusts Kailong Liu overall

1. Yi Li
2. Xiaosong Hu
3. Zhongbao Wei

Papers from Kailong Liu's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework (IEEE Transactions on Instrumentation and Measurement)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Prognostics of lithium-ion batteries based on DempsterShafer theory and the Bayesian Monte Carlo me
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. A review on prognostics and health monitoring of Li-ion battery
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. An integrated approach to battery health monitoring using bayesian regression and state estimation (2007 IEEE Autotestcon)
10. Differential thermal voltammetry for tracking of degradation in lithium-ion batteries

Their papers

• A brief review on key technologies in the battery management system of electric vehicles (2018) — 525 citations
• Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019) — 1,002 citations
• State estimation for advanced battery management: Key challenges and future trends (2019) — 776 citations
• Battery incremental capacity curve extraction by a two-dimensional Luenberger–Gaussian-moving-average filter (2020) — 84 citations
• Gaussian Process Regression With Automatic Relevance Determination Kernel for Calendar Aging Prediction of Lithium-Ion Batteries (2020) — 308 citations
• A Data-Driven Approach With Uncertainty Quantification for Predicting Future Capacities and Remaining Useful Life of Lithium-ion Battery (2021) — 602 citations
• Co-Estimation of State-of-Charge and State-of- Health for Lithium-Ion Batteries Using an Enhanced Electrochemical Model (2022) — 332 citations
• Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures (2020) — 469 citations
• Co-estimation of lithium-ion battery state of charge and state of temperature based on a hybrid electrochemical-thermal-neural-network model (2020) — 328 citations