Areas of expertise

  • Electric and Hybrid Vehicles
  • Mechatronics & Advanced Controls
  • On-Road Vehicle Dynamics
  • Low Carbon Technology
  • Vehicle Engineering & Mobility


Dr Abbas Fotouhi is a Senior Lecturer in Advanced Vehicle Engineering Centre at Cranfield University. He has more than fifteen years research experience in dynamical systems modelling, simulation, optimization, and control. He has also extensive practical and algorithmic experience of applying Artificial Intelligence and Machine Learning techniques in engineering problems. Before joining Cranfield, he was with the Centre for Artificial Intelligence and Robotics (CAIRO) at University Technology Malaysia. His current research is more focused on vehicular systems including hybrid and electric vehicle powertrain systems, energy storage technologies and autonomous cars. He is also interested in applications of AI and machine learning in Intelligent Transportation Systems.

Dr Fotouhi is part of the academic panel who lead MSc courses in Connected and Autonomous Vehicles, Automotive/Motorsport Mechatronics and Automotive Engineering at Cranfield University. He has supervised more than 40 MSc and PhD students and his total writing portfolio lists over 50 publications. After joining Cranfield University, Dr Fotouhi has been also heavily involved in research bid development with a total projects’ cost of over £20m, where he was successful to contribute to more than £1.9m income generation as an investigator (PI or Co-I). He is an editorial board member of Neural Computing and Applications Journal, editorial board member of the Journal of Smart Science, associate editor of International Journal of Strategic Engineering and guest editor of International Journal of Powertrain (IJPT) and journal of Energies. Dr Fotouhi is a Fellow of the UK Higher Education Academy, Fellow of the Faraday Institution in UK, and Senior Member of IEEE.

Research opportunities

MSc by research and PhD opportunities are available in the following main areas:

* Electric and Hybrid Electric Vehicles

* Vehicle Autonomy and ADAS

* Intelligent Transportation Systems

* Applied AI and Machine Learning

If you are interested in any of those topics or you may have your own idea, please first email me to discuss it. To apply for a PhD position, fill in our online application form at, mentioning your preferred supervisor's name on the form.  Advanced Vehicle Engineering is part of our Transport Systems 'theme', so don't worry if the application form has this as the subject area.

Students are normally expected to identify their own source of funding, e.g. an employer or a nationally-funded scholarship.  From time to time, we have funding for PhD scholarships - we always advertise these at 

Current activities


MSc modules in Automotive Engineering and Motorsport.

Selected lectures:

  1. Transport systems optimisation

  2. Vehicle battery technology

  3. Introduction to AI and machine learning

  4. Black-box modelling technique

  5. Introduction to MATLAB programming

Research areas:

  • Energy storage systems - battery HIL test, battery modelling and state estimation, lithium-sulfur battery.

  • Advanced vehicular technologies - EV and HEV powertrain design, optimization and control, automated driving and autonomous cars.

  • Intelligent transportation systems - vehicle-terrain interactions, fleet management systems, driving cycle development.

  • Artificial intelligence and machine learning - applications of AI and ML in transport systems, intelligent mobility, Motorsport.

Research projects:

  • Innovate UK Project, NGB – Next Generation Battery, 2021-2023.
  • Faraday Institution Fellowship project (FIIF-003), AI-BTMS - Artificial Intelligence for Battery Thermal Management System, 2020-2021.
  • EPSRC Project (EP/T006382/1): Novel Unsteady Conjugate Cooling Mechanism, 2020-2022.
  • Innovate UK Project (Reference No. 48727), CHIMERA – an intelligent battery management architecture for next generation electric vehicle batteries using multiple cell chemistries, 2019-2021.
  • Innovate UK Project (Reference No. 105297), ICP – Developing the Isothermal Control Platform as the Basis of New Proposed Standards for the Testing of Lithium Batteries for Use in EVs, 2019-2021.
  • Horizon 2020 Project (grant agreement ID 814471), LISA: Lithium Sulfur for Safe Road Electrification, 2019-2022.
  • Innovate UK Project (TS/R013780/1) LiS:FAB - Lithium Sulfur: Future Automotive Battery (Advanced State Estimation and Management Algorithms, 2018-2021.
  • Horizon 2020 Project (grant agreement ID 666157) ALISE: Advanced Lithium Sulfur Battery for xEV, 2018-2019.
  • EPSRC IAA, Commercial deployment of model and estimator calibration techniques for Li-S battery management algorithms.
  • ATI Project (TS/P003818/1) Zephyr Innovation Programme (ZIP) - development and integration of novel lithium-sulfur battery management and state estimation algorithms for UAVs, 2017-2019.
  • EPSRC Project (EP/L505286/1) Revolutionary Electric Vehicle Battery (REVB) - design and integration of novel state estimation/control algorithms & system optimisation techniques, 2014-2017.

Dr Fotouhi’s team:

  • Zihao (Oscar) Bai (PhD candidate in Automated Decision Making for Autonomous Vehicles at Roundabouts)
  • Xuze (Lewis) Liu (PhD candidate in Formula-E Racing Strategy Development Using Machine Learning)
  • Hanwen Zhang (PhD candidate in Battery Thermal Management System Using Artificial Intelligence)
  • Ibrahim Kasar (PhD candidate in Intelligent Control of High-Temperature Solid Oxide Fuel Cells)
  • Nicolas Valencia Contecha (Research Assistant in in Battery Management Algorithms)


Research Fellows & Research Assistants:

  • Dr Z. Wang (2018-2020, Research Fellow in Li-S battery state estimation – ALISE H2020 Project and ICP Innovate UK Project)
  • Dr Mehdi Soleymani (2018-2021, Research Fellow in Electric Vehicle Battery Management Algorithms – LiSFAB Innovate UK Project)

PhD Students:

  • Dr Chun-wei Chang (2017-2020, PhD title: Human-like Motorway Lane Change Control for AVs)
  • Dr Zhaozhong Zhang (2016-2020, PhD title: Driver Distraction Detection using Machine Learning)

MSc Students:

Irmiya Inniyaka (2015-16), Lu Zhang (2016-17), Rahul Khatry (2016-17), Salih Yousif (2017-18), Victor Calvo Serra (2017-18), Javier Biera (2017-18), Momen Abdallatif (2017-18), Zihao Bai (2017-18), Yan Cai (2017-18), Lichao Yang (2017-18), Ayush Maheswari (2017-18), Sayi Kumar (2017-18), Xuze Liu (2017-18), Zhiyu Sun (2018-19), Fanghao Xu (2018-19), Apurv Sharma (2018-19), Varun Pai (2018-19), Hanwen Zhang (2018-19), Ilyes Miri (2018-19), Pradhan Neelakandan (2018-19), Haolin Zheng (2018-19), Alberto Borges Salas (2018-19), Anthony VAN WAMBEKE (2018-19), Markos Papadimitriou (2018-19), Nicolas Valencia Contecha (2019-20), Jiadi (Ed) Yang (2019-20), Antoine Charlet (2019-20), Harshan Ravikumar (2019-20), Alberto Gonzalez (2019-20), Alessandro Schiraldi (2019-20), Lang Mao (2019-20), Marios Papadopoulos (2019-20), Kenneth Fernandes (2020-21), Muralidharan Jayaram (2020-21), Zhongkai Liu (2020-21), Sean Appleton (2020-21), Merzak Ouldali (2020-21).

Visiting Students:

Samriddh Lakhmani (2018), Nikunj Bangad (2018).


Articles In Journals

Conference Papers