301 Xuefu Road, Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, Jiangsu, P.R. China
Master Supervisors
Pei Lei
Sep 11, 2024

Name

Pei Lei

Professional Title

Lecturer

E-mail

pei@ujs.edu.cn

Short Biography

Education Background

Bachelor and Master Degree (2004.9 – 2010.7), Instrument Science, Harbin Institute of Technology

Doctor Degree (2010.9 – 2016.7), Electrical Engineering, Harbin Institute of Technology

Working Experience

Lecturer (2019.6 - now), Automotive Engineering Research Institute, Jiangsu University

Teaching Courses

1. 《Power Battery technology》

2. 《Present and Future of Battery》

Research Fields

1. Battery Whole-life Use

2. Energy Harvest System

Research Projects

1. National Natural Science Foundation of China, Optimization Strategy of Power Sharing among Parallel Energy Storage Units at Different Aging States Based on Modelling of Batteries’ Capacity-loss Trajectories under Coupling Factors

2. Open Fund of China Electric Power Research Institute, On-line and Quantitative Diagnostic for Capacity-loss Mechanisms in Second-use Batteries based on the Extraction of Compound Degradation Characteristics

3. China Postdoctoral Science Foundation, Cumulative recursive calculation method of battery capacity loss under time-varying coupling conditions

Selected Publications

1. Jianing Xu, Tiansi Wang*, Lei Pei*, Shitong Mao, and Chunbo Zhu, Parameter identification of electrolyte decomposition state in lithium-ion batteries based on a reduced pseudo two-dimensional model with Padé approximation, Journal of Power Sources, 2020, 460: 228093 (SCI, TOP)

2. Tiansi Wang, Lei Pei*, Tingting Wang, Rengui Lu, and Chunbo Zhu, Capacity-loss diagnostic and life-time prediction in lithium-ion batteries: Part 1. Development of a capacity-loss diagnostic method based on open-circuit voltage analysis, Journal of Power Sources, 2016, 301: 187-193 (SCI, TOP)

3. Lei Pei*, Tiansi Wang, Rengui Lu, and Chunbo Zhu, Development of a voltage relaxation model for rapid open-circuit voltage prediction in lithium-ion batteries, Journal of Power Sources, 2014, 253: 412-418 (SCI, TOP)

Selected Patents

1. A method for eliminating the influence of low temperature on the internal resistance test of energy storage battery. (China Patent Award, Rank 3)