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 Vehicle Engineering and Transport Systems at Cranfield University. He has 20 years of research experience in Systems Modelling, Simulation, Optimization, and Control. He has also extensive practical and algorithmic experience in applying Artificial Intelligence and Machine Learning techniques to engineering problems. Before joining Cranfield University, he was with the Centre for Artificial Intelligence and Robotics (CAIRO) at University Technology Malaysia (UTM). His current research is focused on Electrified Transport Systems, Batteries for Electric Vehicles, Fleet Management Optimisation, and Autonomous Vehicles.

Dr Fotouhi is part of the academic panel that leads MSc courses in Connected and Autonomous Vehicles, Automotive/Motorsport Mechatronics, and Automotive Engineering at Cranfield University. He has supervised more than 60 MSc students and 7 PhD students, and his total writing portfolio lists over 65 publications. After joining Cranfield University, Dr Fotouhi has been also heavily involved in research bid development with a total project cost of over £20m, where he was successful in contributing to more than £2.1m income generation as an investigator (PI or Co-I). Dr Fotouhi is an Associate Editor of the Automotive Innovation Journal and an editorial board member of the Neural Computing and Applications Journal. He is a Fellow of the UK Higher Education Academy, a Fellow of the Faraday Institution in the UK, and a Senior Member of IEEE.

Research opportunities

Research areas:

· Electrified Transportation Systems - electric vehicles, charging infrastructure, 'well-to-wheel" energy efficiency analysis, EV market penetration challenges, etc.

· Batteries - 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.

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

· Electrified Transportation Systems

· Batteries

· 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, simply 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

Research projects:

· Innovate UK Project, NEXLFP - Next Generation LFP Batteries - Feb 2023 to Jan 2025.

· UKRI, Faraday Institution Fellowship: Artificial Intelligence for Battery Thermal Management System - Phase 2 (AI-BTMS 2) - Collaboration between Delta-Cosworth and Cranfield University, January 2022 to December 2022.

· Innovate UK Project, Bellerophon Rapid Assembly and Disassembly - February 2022 to May 2023.

· Innovate UK Project, NGB - Next Generation Battery - January 2022 to December 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)

· Hanwen Zhang (PhD candidate in Battery Thermal Management System Using Artificial Intelligence)

· You Gong (PhD candidate in Hybrid Battery Systems Using Low-Frequency Discrete Cell Switching)

· Ibrahim Kasar (PhD candidate in Intelligent Control of High-Temperature Solid Oxide Fuel Cells)

· Chenhui Yin (PhD candidate in trajectory prediction of road users and human-like navigation of autonomous vehicles in urban driving scenarios)

· Rusen Alp Akpinar (PhD candidate in Battery Temperature Prediction Using Machine Learning)


Research Fellows & Research Assistants:

· Nicolas Valencia Contecha (2020-2022, Research Assistant in Battery Management Algorithms - LiSFAB Innovate UK Project and LISA H2020 project)

· 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 Xuze (Lewis) Liu (2019-2022, PhD title: Formula-E Racing Strategy Development Using Machine Learning)

· 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), Werner Tapissier (2021-22), Chi Sun (2021-22), Po-Wei (2021-22), Rohithraj Nagarajan (2021-22), Jaime Ribelles Fayos (2021-22), Siva C M Pandian (2021-22), Yash Yardi (2021-22), Jibin Baby (2021-22), Ben Joseph (2021-22), Gbenga E Adesanya (2021-22), Venkatesh Ragunathan (2021-22), Kesava Kumar Yadala (2021-22), Abhijith Sreekumar (2021-22).

Visiting Students:

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


Articles In Journals

Conference Papers