Areas of expertise
- Electric and Hybrid Vehicles
- Mechatronics & Advanced Controls
- Vehicle Engineering & Mobility
Background
Dr Abbas Fotouhi is a Reader in Vehicle Engineering and Transport Systems at Cranfield University. He has over 20 years of research experience in systems modelling, simulation, optimisation, and control. He also has 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 70 MSc students and 9 PhD students, and his total writing portfolio lists over 80 publications. After joining Cranfield University, Dr Fotouhi has also been heavily involved in research bid development with a total project cost of over £20m, where he was successful in contributing to more than £2.2m income generation as an investigator (Co-I or PI). 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. In 2025, Dr Fotouhi won the Young Global Leadership Award in Applied AI in Engineering, in the House of Lords, London, UK.
Research opportunities
Research areas:
· Electrified Transportation Systems – electric vehicles, charging infrastructure, “well-to-wheel" energy efficiency analysis, EV market penetration challenges, etc.
· Batteries - battery testing, battery modelling and state estimation, lithium-sulfur battery.
· Advanced vehicular technologies - EV and HEV powertrain design, optimisation 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, Automotive and Motorsport Engineering.
MSc by research and PhD opportunities:
If you are interested in any of the above-listed topics or you may have your own idea, please first email me to discuss it. To apply for a PhD in Automotive, Energy and Photonics, simply fill in our online application form here (Cranfield University - Online applications), mentioning your preferred supervisor's name on the form.
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, which are always advertised publicly on the university website.
Current activities
Research Projects:
· Transport Research and Innovation Grants (TRIG), Intelligent Integrated Charging Infrastructure for the UK Ports Energy Management, Funded by Connected Places Catapult and Department for Transport in the UK – Oct 2025 to March 2026.
· Innovate UK Project (10078104), HiCAM – High-performance LFP Cathode Active Material - Jan 2024 to April 2026.
· UKRI Faraday Institution Project (FIRG083), LiSTAR – Lithium-Sulfur Technology Accelerator - June 2023 to April 2026.
· Innovate UK Project (10086686), SHIELD – State of Health, Including Evaluating Longevity Determination of batteries - Jan 2024 to April 2025.
· Innovate UK Project, NEXLFP – Next Generation LFP Batteries - Feb 2023 to Jan 2025.
· Transport Research and Innovation Grants (TRIG), Multi-Vessel Charging Optimisation Platform Under Travel Time and Power Grid Limitations (Multi-Charge), Funded by Connected Places Catapult and Department for Transport in the UK – Oct 2024 to March 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:
· Simha Sreekar Achanta (Research Assistant in Battery Testing, Modelling and Estimation – HiCAM Innovate UK / APC project)
· Rusen Alp Akpinar (PhD candidate in Battery Temperature Prediction Using Machine Learning)
· Yucheng Tan (PhD candidate in Battery Thermal Runaway Prediction Using Machine Learning)
· Yubo Wang (PhD candidate in Maritime Vessels Charging Optimisation)
Alumni
Research Fellows & Research Assistants:
· Dr Hanwen Zhang (2022-2024, Research Fellow in Battery Testing, Modelling and Estimation – NEXLFP Innovate UK project)
· Dr Ibrahim Kasar (2024, Research Assistant in Battery and Fuel Cell Testing – HiCAM Innovate UK / APC project)
· Nicolas Valencia Contecha (2020-2022, Research Assistant in Battery Management Algorithms – LiSFAB Innovate UK Project and LISA H2020 project)
· Dr Dylan 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 Ibrahim Kasar (2021-2025, Intelligent Control of High-Temperature Solid Oxide Fuel Cells)
· Dr Chenhui Yin (2020-2023, Trajectory Prediction of Road Users and Human-like Navigation of Autonomous Vehicles in Urban Driving Scenarios)
· Dr Hanwen Zhang (2019-2022, Battery Thermal Management System Using Artificial Intelligence)
· Dr Zihao (Oscar) Bai (2019-2022, Automated Decision Making for Autonomous Vehicles at Roundabouts)
· Dr You Gong (2019-2022, Hybrid Battery Systems Using Low-Frequency Discrete Cell Switching)
· 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), Baptiste Carron (2022-23), Nrusimhan Seshadri (2022-23), Yubo Wang (2022-23), Yucheng Tan (2022-23), Simha Sreekar Achanta (2022-23), Dhruv Mehta (2022-23), Li-Wei Li (2022-23), Hortense Cledat De La Vigerie (2023-24), Bhagyesh Kishor Wavekar (2023-24), Gabriel Guerin Almazor (2023-24), Rohit Joshi (2023-24), Yadnyesh Mahajan (2023-24), Sun Haoyang (2023-24), Su Xin (2023-24), Sai Mithun Sureshkumar (2023-24), Albert Cases I Pomer (2023-24), Bryan Bou Najm (2024-25), Kingly Lau (2024-25), Mahidhar Ramayanam (2024-25), Hanqi Wang (2024-25), Rohit Shyson Vattaparambil (2024-25).
Visiting Students:
Dr Wensa Wang (2023), Dr Lin Li (2022), Dr Jie Li (2021), Samriddh Lakhmani (2018), Nikunj Bangad (2018).
Publications
Articles In Journals
- Kasar I, Fotouhi A & Nabavi SA. (2025). Performance test of a hydrogen-powered solid oxide fuel cell system and its simulation for vehicle propulsion application. Journal of Cleaner Production, 486
- Yin C, Cecotti M, Auger DJ, Fotouhi A & Jiang H. (2025). Deep‐learning‐based vehicle trajectory prediction: a review. IET Intelligent Transport Systems, 19(1)
- Achanta SS, Fotouhi A, Zhang H & Auger DJ. (2025). Thermal modelling and temperature estimation of a cylindrical lithium iron phosphate cell subjected to an automotive duty cycle. Batteries, 11(4)
- Yin C, Cecotti M, Auger DJ, Fotouhi A & Jiang H. (2025). Lane centerline extraction based on surveyed boundaries: an efficient approach using maximal disks. Sensors, 25(8)
- Li J, Fotouhi A, Liu Y, Zhang Y & Chen Z. (2024). Review on eco-driving control for connected and automated vehicles. Renewable and Sustainable Energy Reviews, 189, Part B
- Zhang H, Fotouhi A, Auger DJ & Lowe M. (2024). Battery temperature prediction using an adaptive neuro-fuzzy inference system. Batteries, 10(3)
- Rodriguez VM, Shateri N, Fotouhi A, Propp K & Auger DJ. (2024). Deterministic observability calculations for zero-dimensional models of lithium–sulfur batteries. Journal of Energy Storage, 87
- Liu X, Fotouhi A & Auger D. (2024). Formula-E multi-car race strategy development—a novel approach using reinforcement learning. IEEE Transactions on Intelligent Transportation Systems, 25(8)
- Liu X, Fotouhi A, Cecotti M & Auger D. (2024). Optimal control of race car with aerodynamic slipstreaming effect. IEEE Transactions on Control Systems Technology, 32(6)
- Cai C, Gong Y, Fotouhi A & Auger DJ. (2024). A novel hybrid electrochemical equivalent circuit model for online battery management systems. Journal of Energy Storage, 99, Part A
- Li J, Liu Y, Cheng J, Fotouhi A & Chen Z. (2024). Eco-driving control for connected plug-in hybrid electric vehicles in urban scenarios with enhanced lane change engagement. Energy, 310
- Li L, Zhao W, Wang C, Fotouhi A & Liu X. (2023). Nash double Q-based multi-agent deep reinforcement learning for interactive merging strategy in mixed traffic. Expert Systems with Applications, 237, Part B(March)
- Li J, Fotouhi A, Pan W, Liu Y, Zhang Y, .... (2023). Deep reinforcement learning-based eco-driving control for connected electric vehicles at signalized intersections considering traffic uncertainties. Energy, 279(September)
- Appleton S & Fotouhi A. (2023). A model-based battery charging optimization framework for proper trade-offs between time and degradation. Automotive Innovation, 6(2)
- Li J, Liu Y, Fotouhi A, Wang X, Chen Z, .... (2022). Cooperative ecological adaptive cruise control for plug-in hybrid electric vehicle based on approximate dynamic programming. IEEE Transactions on Vehicular Technology, 72(3)
- Gong Y, Auger DJ, Fotouhi A & Hale CJ. (2022). A new topology for electric all-terrain vehicle hybrid battery systems using low-frequency discrete cell switching. IEEE Transactions on Transportation Electrification, 9(1)
- Valencia N, Fotouhi A, Shateri N & Auger DJ. (2022). Development of a hybrid adaptive neuro-fuzzy inference system with coulomb-counting state-of-charge estimator for lithium–sulphur battery. International Journal of Fuzzy Systems, 25(2)
- Shateri N, Auger DJ, Fotouhi A & Brighton J. (2022). Charging characterization of a high‐capacity lithium‐sulfur pouch cell for state estimation–an experimental approach. Energy Storage, 5(3)
- Liu X, Fotouhi A & Auger DJ. (2022). Energy-optimal overtaking manoeuvres of Formula-E cars. Vehicle System Dynamics, 61(8)
- Liu X, Fotouhi A & Auger DJ. (2022). Application of advanced tree search and proximal policy optimization on formula-E race strategy development. Expert Systems with Applications, 197(July)
- Shateri N, Auger DJ, Fotouhi A, Brighton J, Du W, .... (2022). Investigation of the effect of temperature on lithium-sulfur cell cycle life performance using system identification and x-ray tomography. Batteries & Supercaps, 5(8)
- Shateri N, Auger DJ, Fotouhi A, Brighton J, Du W, .... (2022). Cover Feature: Investigation of the Effect of Temperature on Lithium‐Sulfur Cell Cycle Life Performance Using System Identification and X‐Ray Tomography (Batteries & Supercaps 8/2022). Batteries & Supercaps, 5(8)
- Shateri N, Auger DJ, Fotouhi A & Brighton J. (2021). An experimental study on prototype lithium-sulfur cells for ageing analysis and state-of-health estimation. IEEE Transactions on Transportation Electrification, 7(3)
- Mao L, Fotouhi A, Shateri N & Ewin N. (2021). A multi-mode electric vehicle range estimator based on driving pattern recognition. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 236(6)
- Zhang Z, Velenis E, Fotouhi A, Auger DJ & Cao D. (2021). Driver distraction detection using machine learning algorithms – an experimental approach. International Journal of Vehicle Design, 83(2/3/4)
- Liu X, Fotouhi A & Auger DJ. (2021). Formula-E race strategy development using distributed policy gradient reinforcement learning. Knowledge-Based Systems, 216(March)
- Shateri N, Shi Z, Auger DJ & Fotouhi A. (2020). Lithium-sulfur cell state of charge estimation using a classification technique. IEEE Transactions on Vehicular Technology, 70(1)
- Liu X, Fotouhi A & Auger DJ. (2020). Optimal energy management for formula-E cars with regulatory limits and thermal constraints. Applied Energy, 279
- Dörfler S, Walus S, Locke J, Fotouhi A, Auger DJ, .... (2020). Recent progress and emerging application areas for lithium-sulfur battery technology. Energy Technology, 9(1)
- Liu X & Fotouhi A. (2020). Formula-E race strategy development using artificial neural networks and Monte Carlo Tree Search. Neural Computing and Applications, 32(18)
- Calvo-Serra V, Fotouhi A, Soleymani M & Auger DJ. (2020). How suitable is lithium-sulphur battery for electric city bus application?. International Journal of Powertrains, 9(4)
- Cao D, Fotouhi A, Auger DJ, Zhang Z & Velenis E. (2020). Driver distraction detection using machine learning algorithms: an experimental approach. International Journal of Vehicle Design, 83(2/3/4)
- Propp K, Auger DJ, Fotouhi A, Marinescu M, Knap V, .... (2019). Improved state of charge estimation for lithium-sulfur batteries. Journal of Energy Storage, 26
- Fotouhi A, Shateri N, Laila DS & Auger DJ. (2019). Electric vehicle energy consumption estimation for a fleet management system. International Journal of Sustainable Transportation, 15(1)
- Muriel JB & Fotouhi A. (2019). Electric vehicle fleet management using ant colony optimisation. International Journal of Strategic Engineering, 3(1)
- Knap V, Auger DJ, Propp K, Fotouhi A & Stroe D-I. (2018). Concurrent real-time estimation of state of health and maximum available power in lithium-sulfur batteries. Energies, 11(8)
- Knap V, Stroe D-I, Purkayastha R, Walus S, Auger DJ, .... (2018). Reference performance test Methodology for degradation assessment of lithium-sulfur batteries. Journal of The Electrochemical Society, 165(9)
- Fotouhi A, Propp K, Samaranayake L, Auger DJ & Longo S. (2018). A hardware-in-the-loop test rig for development of electric vehicle battery identification and state estimation algorithms. International Journal of Powertrains, 7(1/2/3)
- Knap V, Stroe D-I, Christensen AE, Propp K, Fotouhi A, .... (2017). Self-balancing feature of Lithium-Sulfur batteries. Journal of Power Sources, 372
- Fotouhi A, Auger DJ, Propp K & Longo S. (2017). Lithium-sulfur battery state-of-charge observability analysis and estimation. IEEE Transactions on Power Electronics, 33(7)
- Yousif SEA, Fotouhi A, Auger DJ & Propp K. (2017). Self-discharge effects in lithium-sulfur equivalent circuit networks for state estimation. Journal of The Electrochemical Society, 165(1)
- Fotouhi A, Auger DJ, O’Neill L, Cleaver T & Walus S. (2017). Lithium-Sulfur battery technology readiness and applications – a review. Energies, 10(12)
- Fotouhi A, Auger DJ, Propp K, Longo S, Purkayastha R, .... (2017). Lithium-sulfur cell equivalent circuit network model parameterization and sensitivity analysis. IEEE Transactions on Vehicular Technology, 66(9)
- Propp K, Auger DJ, Fotouhi A, Longo S & Knap V. (2017). Kalman-variant estimators for state of charge in lithium-sulfur batteries. Journal of Power Sources, 343
- Fotouhi A, Auger DJ, Propp K & Longo S. (2016). Accuracy versus simplicity in online battery model identification. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(2)
- Propp K, Fotouhi A, Knap V & Auger DJ. (2016). Design, build and validation of a low-cost programmable battery cycler. ECS Transactions, 74(1)
- Propp K, Marinescu M, Auger DJ, O'Neill L, Fotouhi A, .... (2016). Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries. Journal of Power Sources, 328
- Fotouhi A, Auger DJ, Propp K, Longo S & Wild M. (2015). A review on electric vehicle battery modelling: from lithium-ion toward lithium–sulphur. Renewable and Sustainable Energy Reviews, 56
- Fotouhi A, Yusof R, Rahmani R, Mekhilef S & Shateri N. (2014). A review on the applications of driving data and traffic information for vehicles׳ energy conservation. Renewable and Sustainable Energy Reviews, 37
- Fotouhi A & Montazeri-Gh M. (2013). Tehran driving cycle development using the k-means clustering method. Scientia Iranica, 20(2)
- Montazeri M, Fotouhi A & Naderpour A. (2012). Driving segment simulation for determination of the most effective driving features for HEV intelligent control. Vehicle System Dynamics, 50(2)
- Fotouhi A & Montazeri GM. (2012). An investigation on vehicle's fuel consumption and exhaust emissions in different driving conditions. International Journal of Environmental Research, 6(1)
- Montazeri-Gh M & Fotouhi A. (2011). Traffic condition recognition using the -means clustering method. Scientia Iranica, 18(4)
- Montazeri-Gh M, Fotouhi A & Naderpour A. (2011). Driving patterns clustering based on driving features analysis. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 225(6)
Conference Papers
- Akpinar RA, Achanta S, Fotouhi A, Zhang H & Auger DJ. (2024). Battery temperature prediction in electric vehicles using Bayesian regularization
- Wang Z, Fotouhi A & Auger DJ. (2020). State of charge estimation in lithium-sulfur cells Using LSTM recurrent neural networks
- Miri I, Fotouhi A & Ewin N. (2020). Electric vehicle energy consumption modelling and estimation—A case study
- Munisamy S, Auger DJ, Fotouhi A, Hawkes B & Kappos E. (2020). State of energy estimation in electric propulsion systems with lithium-sulfur batteries
- Knap V, Stroe DI, Purkayastha R, Walus S, Auger DJ, .... (2018). Methodology for assessing the lithium-sulfur battery degradation for practical applications
- Fotouhi A, Auger DJ, Propp K & Longo S. (2017). Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies
- Fotouhi A, Auger DJ, Propp K & Longo S. (2016). Influence of battery capacity on performance of an electric vehicle fleet
- Fotouhi A, Shateri N, Auger DJ, Longo S, Propp K, .... (2016). A MATLAB graphical user interface for battery design and simulation; from cell test data to real-world automotive simulation
- Fotouhi A, Auger DJ, Propp K & Longo S. (2016). A study on battery model parametrisation problem: application-oriented trade-offs between accuracy and simplicity
- Fotouhi A, Auger DJ, Propp K & Longo S. (2016). Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies
- Fotouhi A, Propp K & Samaranayake L. (2016). Electric vehicle battery management algorithm development using a HIL simulator incorporating three-phase machines and power electronics
- Fotouhi A, Propp K & Auger DJ. (2015). Electric vehicle battery model identification and state of charge estimation in real world driving cycles
- Propp K, Fotouhi A & Auger DJ. (2015). Low-cost programmable battery dischargers and application in battery model identification
- Fotouhi A, Propp K, Longo S & Auger DJ. (2014). Simulation for prediction of vehicle efficiency, performance, range and lifetime: A review of current techniques and their applicability to current and future testing standards
- Fotoohi A & Yousefi-Koma A. (2006). Improve Hunting of a Railway Vehicle Using Semi-Active Primary Suspension
- Fotoohi A, Yousefi-Koma A & Yasrebi N. (2006). Active control of train bogies with MR dampers
- Fotouhi A & Yousefi-Koma A. (2006). Semi-active train bogie suspension using skyhook dampers
Books
- Ayadi F, Auger DJ, Fotouhi A & Shateri N. (2022). State estimation methodologies for lithium-sulfur battery management systems In Kumta P, Hepp A, Datta M & Velikokhatnyi O (eds), Lithium-Sulfur Batteries. Elsevier.
- Auger DJ, Fotouhi A, Propp K & Longo S. (2019). Battery Management Systems – State Estimation for Lithium–Sulfur Batteries In Wild M & Offer GJ (eds), Lithium Sulfur Batteries. Wiley.
- Fotouhi A, Propp K, Auger DJ & Longo S. (2018). Behaviour of Lithium-Ion Batteries in Electric Vehicles In Pistoia G & Liaw B (eds), Green Energy and Technology (1, 0). Springer International Publishing.
