Areas of expertise
- Computing, Simulation & Modelling
- Electric and Hybrid Vehicles
- Mechatronics & Advanced Controls
- Systems Engineering
- Vehicle Engineering & Mobility
Background
Daniel J. Auger has a background in electrical engineering and applied control & estimation theory. His research looks at ways to exploit estimation and control techniques in vehicle and energy storage applications, particularly in the context of fast model calibration and battery management. Daniel uses carefully designed hardware-in-the-loop experiments to replicate real-world battery behaviours early in a product lifecycle, and then uses formal system identification techniques, control-oriented estimation techniques and computer science to produce models and state estimation software for incorporation in real-time battery management systems.
Daniel is currently working on the application of reduced-order physics-based models for fast model calibration and estimation, control of hybrid battery systems, electrical and module/pack-level thermal modelling and state estimation, and prognostic/diagnostic techniques for predicting and assessing battery health and remaining useful life.
Daniel teaches on the motorsport and automotive MSc programme, and is module lead for Automotive Control and Simulation and Advanced Control and Optimisation.
Before joining Cranfield, he worked in senior control engineering roles in BAE Systems and MathWorks Consulting Services. He has MEng and PhD degrees from Cambridge and is a chartered engineer, an IET Fellow and an IEEE Senior Member; he holds the FHEA university teaching qualification.
Current activities
Green Futures Investment Limited Technology Accelerator Fund Project. Early detection and warning system for lithium battery thermal runaway. £50k. PI. Co-Is Dr A Fotouhi, Dr G Gratton.
Faraday Battery Challenge Project. SHIELD: State of Health Including Evaluating Longevity Determination of batteries. £99,982 (Cranfield part). Jan 24 - Dec 24. Cranfield Lead. Co-I Dr A Fotouhi.
Faraday Institution Project. LiSTAR Phase 2. £221,219 (Cranfield part). Apr 23 - Mar 25. Cranfield Lead. PI Prof P Shearing (formerly UCL, now Oxford). Co-Is include Dr A Fotouhi.
Innovate UK Project (10017550). BRAD: Bellerophon Rapid Assembly and Disassembly, £115,495 (Cranfield part). Feb 22 - Apr 23. Cranfield Lead. Co-I Dr A Fotouhi.
Innovate UK Project (83328): NGB: NexGen Battery, £120,424 (Cranfield part). Jan 22 - Dec 23. Cranfield Lead Dr A Fotouhi. Co-I Dr DJ Auger
Innovate UK Project (78920). SLB4ComEU: Second-Life Batteries for Commercial End-Use, £99,930 (Cranfield part). Sep 20 - Jul 21. Cranfield Lead Dr C Long. Co-Is Dr D Auger, Dr J Luo.
Horizon 2020 Project (814471) LISA: Lithium Sulfur for Safe Road Vehicle Electrification, EUR 562,513 (Cranfield part), Jan 19 to Dec 2022. Cranfield Lead. Co-Is Dr A Fotouhi, Prof J Brighton.
Innovate UK Project (48727) Chimera: an intelligent battery management architecture for next-generation electric vehicle batteries using multiple cell chemistries, £82,558 (Cranfield part), Jun 20 - Nov 21. Cranfield Lead. Co-I Dr A Fotouhi.
Innovate UK Project (TS/R013780/1) LiS:FAB - Lithium Sulfur: Future Automotive Battery (Advanced State Estimation and Management Algorithms, £859,504 (Cranfield part), Apr 18 to Sep 21. Cranfield Lead. Co-Is Dr A Fotouhi, Prof J Brighton.
Innovate UK Project (105297) Developing the Isothermal Control Platform (ICP) as the Basis of New Proposed Standards for the Testing of Lithium Batteries for Use in Electric Vehicles, £82,205 (Cranfield part), Jul 19 - Jun 21. Cranfield Lead. Co-I Dr A Fotouhi.
Horizon 2020 Project (666157) ALISE: Advanced Lithium Sulfur Battery for xEV, EUR 111,717 (Cranfield part), Mar 18 - May 2019. Cranfield Lead. Co-I Dr A Fotouhi.
ATI Project (TS/P003818/1) Zephyr Innovation Programme (ZIP) - development and integration of novel lithium-sulfur battery management and state estimation algorithms for UAVs, £245,135, May 17 - Dec 18. Cranfield Lead. Co-Is Dr S Longo, Dr A Fotouhi.
Innovate UK Project (TS/P012000/1) HumanDRIVE, £1,199,941, Jan 17 - Dec 19, Cranfield Leads Prof A Tsourdos, Prof JL Brighton, Co-Is Dr A Savvaris, Prof R Zbikowski, Dr DJ Auger, Dr S Longo, Dr A Soltani.
EPSRC Project (EP/N012089/1) TASCC: Driver-cognition-oriented optimal control authority shifting for adaptive automated driving (CogShift), £1,587,193, Dec 15 - Dec 19, PI Prof JL Brighton, Co-Is Prof N Lavie, Dr DJ Auger, Dr Y Zhao.
EPSRC Project (EP/L505286/1) Revolutionary Electric Vehicle Battery (REVB) - design and integration of novel state estimation/control algorithms & system optimisation techniques, £468,617, Feb 14 - Apr 17, Cranfield Lead Dr D Auger, Co-I Dr S Longo.
EPSRC Project (EP/I038586/1) Developing FUTURE Vehicles (Fundamental Understanding of Technologies for Ultra Reduced Emission Vehicles), £3,012,029, [Jan 13] - May 16, PI Prof R Thring, Co-Is Prof Q Zhong, Prof DA Stone, Prof K Burnham, Prof NP Brandon, Prof D Howey, Dr T Larkowski, Dr D J Auger, Dr S Longo, Dr M Sumislawska, Prof M McCulloch, Professor R Martinez-Botas, Dr J Marco, Dr G Offer, Prof F Assadian.
Clients
Current and recent grants have been provided by Innovate UK, The European Commission, EPSRC, the Aerospace Technology Institute (ATI) and The Faraday Institution.
Current and recent collaborators include OXIS Energy, The LEITAT Technological Center, Thermal Hazard Technologies and Chimera Energy.
Publications
Articles In Journals
- 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) - 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)
- Liang C, Xu X, Auger DJ, Wang F & Wang S. (2023). Efficient Mode Transition Control for DM-PHEV With Mechanical Hysteresis Based on Piecewise Affine H ∞ Strategy. IEEE Transactions on Transportation Electrification, 9(3)
- 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)
- Hales A, Brouillet E, Wang Z, Edwards B, Samieian MA, .... (2021). Isothermal Temperature Control for Battery Testing and Battery Model Parameterization. SAE International Journal of Alternative Powertrains, 7(2)
- 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
- 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)
- 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
- 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)
- 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)
- 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)
- Lv C, Wang H, Cao D, Zhao Y, Auger DJ, .... (2018). Characterization of Driver Neuromuscular Dynamics for Human–Automation Collaboration Design of Automated Vehicles. IEEE/ASME Transactions on Mechatronics, 23(6)
- Lv C, Cao D, Zhao Y, Auger DJ, Sullman M, .... (2018). Analysis of autopilot disengagements occurring during autonomous vehicle testing. IEEE/CAA Journal of Automatica Sinica, 5(1)
- 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
- Zhao Y, Görne L, Yuen I-M, Cao D, Sullman M, .... (2017). An Orientation Sensor-Based Head Tracking System for Driver Behaviour Monitoring. Sensors, 17(11)
- 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)
- Othaganont P, Assadian F & Auger DJ. (2017). Multi-objective optimisation for battery electric vehicle powertrain topologies. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 231(8)
- 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)
- Papazoglou A, Longo S, Auger D & Assadian F. (2014). Nonlinear Filtering Techniques Comparison for Battery State Estimation. Journal of Sustainable Development of Energy, Water and Environment Systems, 2(3)
- Longo S, Auger DJ & Assadian F. (2014). Mechatronics in Sustainable Mobility: Two Electric Vehicle Applications. The Journal of Sustainable Mobility, 1(1)
- Othaganont P, Assadian F & Auger D. (2014). Sensitivity Analyses for Cross-Coupled Parameters in Automotive Powertrain Optimization. Energies, 7(6)
- J. Auger D, F. Groff M, Mohan G, Longo S & Assadian F. (2014). Impact of Battery Ageing on an Electric Vehicle Powertrain Optimisation. Journal of Sustainable Development of Energy, Water and Environment Systems, 2(4)
Conference Papers
- Cai C, Auger DJ & Perinpanayagam S. (2023). Enhanced online identification of battery models exploiting data richness
- Munisamy S, Auger DJ, Fotouhi A, Hawkes B & Kappos E. (2021). STATE OF ENERGY ESTIMATION IN ELECTRIC PROPULSION SYSTEMS WITH LITHIUM-SULFUR BATTERIES
- Yang L, Semiromi MB, Auger D, Dmitruk A, Brighton J, .... (2020). The implication of non-driving activities on situation awareness and take-over performance in level 3 automation
- Wang Z, Fotouhi A & Auger DJ. (2020). State of Charge Estimation in Lithium-Sulfur Cells Using LSTM Recurrent Neural Networks
- Lv C, Wang H, Cao D, Zhao Y, Sullman M, .... (2018). A Novel Control Framework of Haptic Take-Over System for Automated Vehicles
- Morganti MV, Longo S, Tirovic M, Auger DJ & Shah Bin Raja Ahsan RM. (2018). Modular Battery Cell Model for Thermal Management Modelling
- Lv C, Wang H, Cao D, Zhao Y, Auger DJ, .... (2017). Characterisation of driver neuromuscular dynamics for haptic take-over system design for automated vehicles
- 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
- Amy T, Kong H, Auger D, Offer G & Longo S. (2016). Regularized MPC for Power Management of Hybrid Energy Storage Systems with Applications in Electric Vehicles * *Supported by the "Developing FUTURE Vehicles" project of the British Engineering and Physical Sciences Research Council.
- 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
- Al-Jazaeri AO, Samaranayake L, Longo S & Auger DJ. (2014). Fuzzy Logic Control for energy saving in Autonomous Electric Vehicles
- 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
- Feig P, Auger D, Billitteri F & Longo S. (2014). Sensors-models trade-offs in battery state estimation
- Papazoglou A, Longo S, Auger DJ & Assadian F. (2013). Computational Aspects of Estimation Algorithms for Battery-Management Systems
- Auger DJ, Groff MF, Mohan G, Longo S & Assadian F. (2013). The impact of battery ageing on an electric vehicle powertrain optimisation
- Butcher J, Clarke N, Pettitt D, Whitten T, Auger D, .... (2012). Development of adaptable UUV systems using model-based design
- Rottier P & Auger D. (2012). Application of DEF STAN 61-22 to guide development and verification of an electrical power system model
- Auger DJ, Crawshaw S & Hall SL. (2008). Robust H-Infinity Control of a Steerable Marine Radar Tracker
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.
