Collection 

Battery Management Systems for Vehicle Electrification

Submission status
Closed
Submission deadline
The world is actively optimizing and adjusting its energy infrastructure and implementing carbon-neutral policies. Globally, the automotive industry is moving towards electrification and intelligent transformation. The lithium-ion battery is the main energy storage component in electric vehicles due to its high energy density. However, large large-scale lithium-ion batteries still face many challenges.  Degradation, instability at high temperatures, performance degradation at low temperatures, risk of overcharge and over-discharge, and difficulty in fault diagnosis and prognosis, all weaken the market competitiveness of electric vehicles. Monitoring and management are required to ensure safety and reliability during operation. Common tasks of battery management systems include accurate state estimation, battery balancing, safe and efficient charge/discharge strategies, thermal management, fault diagnosis, and prediction.
Advanced battery management systems are expected to improve the performance of the battery at the cell, module, and pack levels. With this in mind, we open this Collection with the goal of developing advanced battery management systems for electric vehicles. The Collection will publish high-quality Research, Reviews Perspectives and Commentary. Potential topics include, but are not limited to, the following research areas:
 
  • Battery management system: design, control and simulation.
  • State estimation: modelling, state estimation including the state of charge, state of health, state of power and energy, equalization, charge/discharge strategy.
  • Thermal management: battery thermal runaway, safety materials, low-temperature heating techniques, thermal management design and strategy
  • Battery degradation: degradation mechanisms, second use, diagnosis and prognosis, health monitoring.
  • Battery safety: failure mechanisms, battery fault detection and diagnosis, Early warning, typical fault root cause and simulation, State of Safety.
  • Fast charging technology and strategies.
  • Advanced techniques at the cell, module, and pack level: machine learning, digital twins, and cloud computing.
  • Advanced experimental and characterization methods.
  • New sensor technologies for future battery management.

 

A white electric car being charged at a charging point

Editors

Dr Weihan LiDr. Weihan Li is a research group leader at RWTH Aachen University. Previously, he was team leader and research associate at RWTH Aachen from 2018 to 2021, where he received his Ph.D. (electrical engineering) with the highest praise “summa cum laude” in 2021. He is the recipient of the Deutscher Studienpreis, Battery Young Research Award and RWTH Start-Up Grant in 2022. The research interests of Weihan Li’s group include the modeling, testing and control of batteries from material level to system level with a wide application of physics-based and machine learning approaches.

 

Billy WuDr. Billy Wu is a Senior Lecturer (Associate Professor) at Imperial College, London, UK and Faraday Institution Industrial Fellow. He works at the interface between fundamental science and engineering application of electrochemical energy devices such as batteries, fuel cells and supercapacitors. Cross cutting activities include: energy materials, continuum modelling, understanding degradation, thermal management, pack design and control.

 

 

Caiping ZhangDr. Caiping Zhang is a Professor at the School of Electrical Engineering, Beijing Jiaotong University, China. She is a recipient of the National Excellent Young Scientists Fund, and Beijing New-star Plan of Science and Technology. Professor Zhang received her PhD from Beijing Institute of Technology in 2010 and was a visiting PhD student at the University of Southampton from 2008 to 2009.  Her research interests include lithium-ion battery multi-physics modeling and states estimation in electric vehicles, battery degradation mechanism and remaining life prediction, fault diagnosis, battery control and optimal charging, battery endurance and reliability management strategy.

 

Jiangong ZhuDr. Jiangong Zhu is an Associate Professor in the School of Automotive Studies at Tongji University, China.  He received the Ph.D. degree in automotive engineering at Tongji University. He was a Post-Doctoral Researcher at the Institute for Applied Materials at the Karlsruhe Institute of Technology (KIT) in Germany. He is a “Humboldtians” Fellow from the support of Humboldt Foundation and a DAAD (Deutscher Akademischer Austausch Dienst) fellow. His research interests include electric vehicles, lithium-ion batteries, battery lifetime and safety management, state estimation, and battery modeling. His current research focus is on applying ex-situ and in-situ methods to investigate battery degradation, and inventing new methods (e.g., machine learning and optimization) to prognose battery state of health and manage lifespan. Jiangong Zhu is an Editorial Board Member of Communications Engineering.