Ji Li

Mr, Dr.

Accepting PhD Students

PhD projects

Warmly welcome individuals with a keen interest in multidisciplinary research in the field of Automotive Engineering. My research encompasses a broad range of topics, including but not limited to Vehicle Energy Management, Driver Behavior Modeling, Data-driven Modeling, Learning Systems, Human-Machine Interaction, Shared Control, Platoon Control, Applied Data Science, Multi-Modal Information Fusion, and Physics-Informed Machine Learning.

One of our current research projects, titled "Human-Like Shared and Autonomous Driving of Future Vehicles," offers an opportunity for external or self-funded PhD students. This project aims to investigate and develop advanced driving systems that emulate human-like behaviors in shared and autonomous vehicles.

For more information about this specific project, please drop me an email: j.li.1@bham.ac.uk or visit the following link: https://www.findaphd.com/phds/project/human-like-shared-and-autonomous-driving-of-future-vehicles/?p157648

20182024

Research activity per year

Personal profile

Biography

Ji Li was awarded a PhD in Mechanical Engineering in 2020 from University of Birmingham, United Kingdom. Prior to being appointed to this position, he spent two years as a Postdoctoral Research Fellow and one year as a Postdoctoral Teaching Fellow at the University of Birmingham.

 

He has been instrumental in the successful delivery of several government and industry research projects (e.g., EP/J00930X/1EP/N021746/1Innovate UK 102253) and established expertise in dedicated AI systems for automotive engineering. He has received major grants from several OEMs and research institutes e.g., BYD Auto Ltd, Jiangsu Industry Technology Research Institute.

 

He has authored over 30 peer-reviewed journal papers, several conference papers, and two book chapters in the field of Connected and Autonomous Vehicles with aspects of multi-objective control, human-machine interaction, and cyber-physical systems.

Research interests

His research focus covers three key domains: multi-objective control, human-machine interaction, and cyber-physical systems, all oriented toward achieving net-zero and trustworthy engineering solutions. The overarching goal is to contribute to developing future vehicles that are not only zero-emission but also trustworthy and adeptly leverage digitalization at various operational levels. The research seeks to address challenges and pave the way for innovative solutions in the dynamic landscape of automotive technology at four observation scales:

 

Lv.1 Component Level: engine/battery/fuel cell

  • Physics/data-enhanced robust modelling
  • Transient calibration and autonomous calibration

Lv.2 Powertrain Level: series/parallel/power-split hybrid

  • Many-objective modular design
  • Learning-based energy management

Lv.3 Vehicle Level: driver/vehicle/road

  • Driving behaviour identification and recognition
  • Human-machine interaction and shared control

Lv.4 Fleet Level: platoon/traffic

  • Car-following behaviour characterization
  • Mixed vehicular platooning

 

Current Project:

  • Development of Dual-mode Engine AI Emission Prediction and Knock Detection, 2022, BYD Auto Company
  • Research on Real-time Optimisation System for Plug-in Hybrid Electric Vehicle based on Artificial Intelligence Digital Twin Technology, 2020, Jiangsu Industry Technology Research Institute
  • AI Strategy for Hybrid Engine Development, 2020, BYD Auto Company

 

Industrial Partnership:

  • BYD Auto Company, Mahler, Changan UK, London Electric Vehicle Company, Joint Research Centre, Lotus Cars Limited, etc.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 7 - Affordable and Clean Energy
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action

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