Areas of expertise
- Electric and Hybrid Vehicles
- Mechatronics & Advanced Controls
- On-Road Vehicle Dynamics
- Low Carbon Technology
- Vehicle Engineering & Mobility
Background
Dr Abbas Fotouhi is a Reader 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 https://tinyurl.com/PhD-in-Transport-Systems, 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 https://tinyurl.com/Transport-Systems-PhD-Funding.
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)
Alumni
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).
Publications
Articles In Journals
- Li L, Zhao W, Wang C, Fotouhi A & Liu X. (2024). Nash double Q-based multi-agent deep reinforcement learning for interactive merging strategy in mixed traffic. Expert Systems with Applications, 237(March)
- 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
- 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, PP(99)
- 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
- Liu X, Fotouhi A & Auger DJ. (2023). Energy-optimal overtaking manoeuvres of Formula-E cars. Vehicle System Dynamics, 61(8)
- Gong Y, Auger DJ, Fotouhi A & Hale CJ. (2023). A New Topology for Electric All-Terrain Vehicle Hybrid Battery Systems Using Low-Frequency Discrete Cell Switching. IEEE Transactions on Transportation Electrification, 9(1)
- Shateri N, Auger DJ, Fotouhi A & Brighton J. (2023). Charging characterization of a
high‐capacity lithium‐sulfur pouch cell for state estimation: An experimental approach. Energy Storage, 5(3) - Li J, Liu Y, Fotouhi A, Wang X, Chen Z, .... (2023). Cooperative Ecological Adaptive Cruise Control for Plug-In Hybrid Electric Vehicle Based on Approximate Dynamic Programming. IEEE Transactions on Vehicular Technology, 72(3)
- Valencia N, Fotouhi A, Shateri N & Auger D. (2023). 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)
- 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, 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)
- Mao L, Fotouhi A, Shateri N & Ewin N. (2022). 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)
- Liu X, Fotouhi A & Auger D. (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, Shi Z, Auger DJ & Fotouhi A. (2021). Lithium-Sulfur Cell State of Charge Estimation Using a Classification Technique. IEEE Transactions on Vehicular Technology, 70(1)
- 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, Auger DJ, Fotouhi A & Brighton J. (2021). An Experimental Study on Prototype Lithium–Sulfur Cells for Aging Analysis and State-of-Health Estimation. IEEE Transactions on Transportation Electrification, 7(3)
- Dörfler S, Walus S, Locke J, Fotouhi A, Auger DJ, .... (2021). Recent Progress and Emerging Application Areas for Lithium–Sulfur Battery Technology. Energy Technology, 9(1)
- Fotouhi A, Shateri N, Shona Laila D & Auger DJ. (2021). Electric vehicle energy consumption estimation for a fleet management system. International Journal of Sustainable Transportation, 15(1)
- Zhang Z, Velenis E, Fotouhi A, Auger DJ & Cao D. (2020). 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. (2020). Optimal energy management for formula-E cars with regulatory limits and thermal constraints. Applied Energy, 279
- 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)
- Auger DJ, Calvo Serra V, Soleymani M & Fotouhi A. (2020). How suitable is lithium-sulphur battery for electric city bus application. International Journal of Powertrains, 9(4)
- Muriel JB & Fotouhi A. (2020). Electric Vehicle Fleet Management Using Ant Colony Optimisation. International Journal of Strategic Engineering, 3(1)
- 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, Auger DJ, Propp K & Longo S. (2018). Accuracy Versus Simplicity in Online Battery Model Identification. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(2)
- Fotouhi A, Auger DJ, Propp K & Longo S. (2018). Lithium–Sulfur Battery State-of-Charge Observability Analysis and Estimation. IEEE Transactions on Power Electronics, 33(7)
- Knap V, Auger D, 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)
- Yousif SEA, Fotouhi A, Auger DJ & Propp K. (2018). Self-Discharge Effects in Lithium-Sulfur Equivalent Circuit Networks for State Estimation. Journal of The Electrochemical Society, 165(1)
- Fotouhi A, Longo S, Propp K, Samaranayake L & Auger D. (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)
- 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
- 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 D, 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, 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. (2016). A review on electric vehicle battery modelling: From Lithium-ion toward Lithium–Sulphur. Renewable and Sustainable Energy Reviews, 56
- Propp K, Fotouhi A, Knap V & Auger DJ. (2016). Design, Build and Validation of a Low-Cost Programmable Battery Cycler. ECS Transactions, 74(1)
- 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 & 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)
- Montazeri-Gh M & Fotouhi A. (2011). Traffic condition recognition using the -means clustering method. Scientia Iranica, 18(4)
Conference Papers
- Miri I, Fotouhi A & Ewin N. (2021). Electric vehicle energy consumption modelling and estimation—A case study
- Munisamy S, Auger DJ, Fotouhi A, Hawkes B & Kappos E. (2021). STATE OF ENERGY ESTIMATION IN ELECTRIC PROPULSION SYSTEMS WITH LITHIUM-SULFUR BATTERIES
- Wang Z, Fotouhi A & Auger DJ. (2020). State of Charge Estimation in Lithium-Sulfur Cells Using LSTM Recurrent Neural Networks
- Fotouhi A, Auger DJ, Propp K & Longo S. (2017). Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li‐S case studies
- Knap V, Stroe DI, Purkayastha R, Walus S, Auger DJ, .... (2017). Methodology for Assessing the Lithium-Sulfur Battery Degradation for Practical Applications
- Fotouhi A, Longo S, Auger DJ & Propp K. (2016). Electric Vehicle Battery Parameter Identification and SOC Observability Analysis: NiMH and Li-S Case Studies
- Fotouhi A, Propp K, Samaranayake L, Auger DJ & Longo S. (2016). Electric vehicle battery management algorithm development using a HIL simulator incorporating three-phase machines and power electronics
- 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, Cleaver T, Shateri N, Propp K, .... (2016). Influence of battery capacity on performance of an electric vehicle fleet
- Fotouhi A, Auger DJ, Propp K & Longo S. (2016). A Study on Battery Model Parametrisation Problem - Application-Oriented Trade-offs between Accuracy and Simplicity
- Propp K, Fotouhi A & Auger DJ. (2015). Low-cost programmable battery dischargers and application in battery model identification
- Fotouhi A, Propp K & Auger DJ. (2015). Electric vehicle battery model identification and state of charge estimation in real world driving cycles
- 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.
