Feng Fei, Assistant research fellow of Chongqing University, China
He received his Ph.D. degree in instrument science and technology from Harbin Institute of Technology, Harbin, China, in 2017. He is currently the Assistant research fellow of the School of Automation, Chongqing University, Chongqing, China, and the Member of the Institution of Engineering and Technology.
Dr. Feng is a leading researcher in fault diagnosis, prognosis and health management for electrochemical energy storage system, significantly contributing to both health management theory methods and engineering applications. He is very active as reviewers for top journals, including IEEE Trans. on Industrial Electronics, IEEE Trans. on Industrial Informatics, IEEE Trans. on Power Electronics. As a scientific leader in the field of fault diagnosis, prognosis and health management, he has been serving on various national and international technical committees.
Dr. Feng has made original contributions in fault diagnosis, prognosis and health management technology for electrochemical energy storage system with real world applications, which can be assessed by his publications (over 20 papers) in prestigious international journals, including Renewable and Sustainable Energy Review, Journal of Power Sources, IEEE Trans. on Transportation Electrification, 2 highly cited papers and more than 550 Google Scholar citations. He also held 20 patents, and 1 software copyright. He has given many keynote talks and invited talks.
Contact Information
Email: feifeng@cqu.edu.cn, ffe423@126.com
Address:Shazheng Street174#, Shapingba District,Chongqing, 400044,China
Webpage: https://scholar.google.com/citations?user=ZHcRCGkAAAAJ&hl=zh-CN
Education
Ph.D., (I.S.T.), Harbin Institute of Technology, P. R. China, 2017.
M.S., (I.S.T.), Harbin Institute of Technology, P. R. China, 2010.
B.S., (M.C.T.I.), Harbin University of Science and Technology, P. R. China, 2008.
Academic Experience
Assistant research fellow, 11/2017- present, Chongqing University, Chongqing, P. R. China
Visiting Scholar, 3/2015 – 2/2016, RWTH Aachen University, Germany
Research Interests
New concept, new theory, new technology and new platform of fault diagnosis, prognosis and health management for electrochemical energy storage system
New concept:
Ø Industry 4.0, Industrial Internet/Internet of Things, Industrial artificial intelligence, Industrial Big Data, Industrial cloud
Ø Cyber-Physical System, Digital twin, Digital Thread
New theory:
Ø Validation and verification technology for new material battery
Ø Massive battery data mining and machine learning theory
Ø The evolution mechanism and modeling of energy storage system
Ø Theory of battery system design, control and optimization
Ø Comprehensive evaluation and decision theory of energy storage system
New technology:
Ø Numerical calculation and simulation technology of energy storage system
Ø Fast charging and efficient balance technology
Ø Advanced sensing and intelligent diagnostic technology
Ø Energy storage system prediction and health management technology
Ø Retired battery resource utilization and management technology
New platform:
Ø Industrial Internet platform technology
Ø Industrial APP development technology
Ø System deployment and integration technology
Applications:
Ø New energy vehicles
Ø Smart grid
Ø Aerospace industry
Ø Rail traffic
Ø Military equipment
Publications
Part I – Referred Journal Papers (selected)
[1] Feng F.*, Sangli T, Kailong L, Jiale X, Yi X, Bo L, Kexin L. Co-estimation of Lithium-ion Battery State of Charge and State of Temperature Based on a Hybrid Electrochemical-Thermal-Neural-Network Model, Journal of Power Sources, 455, 227935, 2020.03.03. (SCI, JCR Q1, IF: 7.467, WOS: 000523640000006, DOI: https://doi.org/10.1016/j.jpowsour.2020.227935, ISSN: 0378-7753, Highly cited papers)
[2] Feng F.*, Hu X., Liu J., Lin X., Liu B. A Review of Equalization Strategies for Series Battery Packs: Variables, Objectives, and Algorithms, Renewable & Sustainable Energy Reviews, 116, 109464, 2019.10.09. (SCI, JCR Q1, IF: 10.556, WOS: 000523392400042, DOI: https://doi.org/10.1016/j.rser.2019.109464, ISSN: 1364-0321)
[3] Feng F.*, Hu X., Hu L., Hu F., Li Y., Zhang L. Propagation Mechanisms and Diagnosis of Parameter Inconsistency within Li-Ion Battery Packs, Renewable & Sustainable Energy Reviews, 112, 102-113, 2019.05.29. (SCI, JCR Q1,IF: 10.556, WOS: 000474208400008,DOI: https://doi.org/10.1016/j.rser.2019.05.042, ISSN: 1364-0321)
[4] Feng F.*, Hu X., Liu K., Che Y., Lin X., Jin G., Liu B. A Practical and Comprehensive Evaluation Method for Series-Connected Battery Pack Models, IEEE Transactions on Transportation Electrification, 6(2), 391-416, 2020.03.27. (SCI,JCR Q1,IF: 5.27, WOS: 000545438200003, DOI:10.1109/TTE.2020.2983846, ISSN: 2332-7782)
[5] Hu L., Hu X*., Che Y., Feng F.*, Lin X., Liu B., Reliable State of Charge Estimation of Battery Packs Using Fuzzy Adaptive Federated Filtering, Applied Energy, 262, 114569, 2020.02.03. (SCI, JCR Q1, IF: 8.426, WOS:000517398200088, DOI: https://doi.org/10.1016/j.apenergy.2020.114569, ISSN: 0306-2619)
[6] Hu X., Feng F., Liu K., Zhang L., Xie J., Liu B. State Estimation for Advanced Battery Management: Key Challenges and Future Trends, Renewable & Sustainable Energy Reviews, 114, 1-13, 2019.08.14. (SCI,JCR Q1,IF: 10.556, WOS:000488871200043,DOI: https://doi.org/10.1016/j.rser.2019.109334, Highly cited papers)
Part II- Conference Papers
[1] Xiao W., Xu H., Jia J., Feng F., Wang W., State of Health Estimation Framework of Li-ion Battery Based on Improved Gaussian Process Regression for Real Car Data, International Conference on Energy, Power and Mechanical Engineering, EPME2019, Guangzhou, China, Dec. 20-22, 2019. (EI,DOI:10.1088/1757-899X/793/1/012063)
[2] Xia zeng, Le Xu, Zhongwei Deng, Fei Feng, Xiaosong Hu. Global Sensitivity Analysis of Battery Single Particle Model Parameters. IEEE Vehicle Power and Propulsion Conference, VPPC, Hanoi, Vietnam, Oct.14-17, 2019. (EI,DOI: 10.1109/VPPC46532.2019.8952424)
[3] Hu X., Jiang H., Feng F., Zou C. A novel multi-scale co-estimation framework of State of Charge, State of Health, and State of Power for lithium-ion batteries. International Conference on Electric and Intelligent Vehicles (ICEIV2018), Melbourne, Australia, Nov.20-25, 2018. (EI, WOS:000468631900053, DOI: 10.12783/dteees/iceee2018/27824)
[4] Fei Feng*, Rengui Lu, Shaojie Zhang, Chunbo Zhu, and Guo Wei, “Temperature characteristics and modelling research on LiFePO4 cells series battery pack in electric vehicles”, The International Conference on Life System Modeling and Simulation and International Conference on Intelligent Computing for Sustainable Energy and Environment, LSMS&ICSEE , Shanghai, China, Sep. 20-23, 2014. (EI :20144500174151, DOI: https://doi.org/10.1007/978-3-662-45286-8_48)
[5] Fei Feng*, Rengui Lu, Guoliang Wu, and Chunbo Zhu, “A Measuring Method of Available Capacity of Li-Ion Series Battery Pack”. IEEE Vehicle Power and Propulsion Conference, VPPC, Seoul, South Korea, Oct.09-12, 2012. (EI :20131016080897, DOI: 10.1109/VPPC.2012.6422667)
Patents (selected)
[1] Feng F., Xie Y., Li K., et al, A joint state estimation method for SOC and SOT of power cells based on the coupled model of electric-thermal neural network, China Invention Patent. AN: CN201911031589.0, AD: 2019-10-28; PN: CN110703114A, PD: 2020-01-17.
[2] Feng F., Hu X., Yang X., et al, A method for predicting the residual life of lithium ion battery based on fusion algorithm, China Invention Patent. AN: CN201910573259.8, AD: 2019-06-27; PN: CN110187290B, PD: 2019-08-30.
[3] Feng F., Hu X., Li J., et al, A method for balancing of lithium ion power battery pack in the life cycle, China Invention Patent. AN: CN201910523087.3, AD: 2019-06-17; PN: CN110247451A, PD: 2019-09-17.
[4] Feng F., Hu X., Li J., et al, A joint state estimation method for dynamic lithium battery based on multi-dimensional coupling model, China Invention Patent. AN: CN201910561982.4, AD: 2019-06-26; PN: CN110161423A, PD: 2019-08-23.
[5] Feng F., Hu X., Hu F., et al, A method for diagnosing parameter inconsistency of power battery pack, China Invention Patent. AN: CN201910373001.3, AD: 2019-05-06; PN: CN110045298A, PD: 2019-07-23.
Research Grants
[1] The key technologies of residual value evaluation and Cascade utilization of retired batteries based on big data, Chongqing entrepreneurship and innovation support fund for returned overseas students (Grant No. cx2019019), China, 2019.09-2021.09. (PI)
[2] Research on key technologies of flexible reuse of retired batteries based on multi-source heterogeneous data, Chongqing special project of basic research and frontier exploration – postdoctoral science fund (Grant No. cstc2019jcyj-bsh0015), China, 2019.03-2021.03. (PI)
[3] Research and development and industrialization of plug-in hybrid electric vehicle control system technology, Chongqing technological innovation and application development - Major theme projects (Grant No. cstc2019jscx-zdztzx0044), China, 2019.09-2022.08. (PI)
[4] Research on Efficient Energy Balance Strategy for Power Battery Pack in the Full Life Cycle, NSFC (No. 51807017), China, 2019.01-2021.12. (PI)
[5] Research on Balance Strategy and States Co-estimation for Power Battery Pack in the Full Life Cycle, Chinese Postdoctoral Science Foundation (No. 2018M643404), China, 2019.01-2021.12. (PI)
Research on basic theory and key technology of balance management of traction battery pack, Special Foundation of Chongqing Postdoctoral Science (No. XmT2018036), China, 2019.01-2021.12. (PI).