Projects
Projects: Projects for Investigator |
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| Reference Number | EP/I038586/1 | |
| Title | Developing FUTURE Vehicles (Fundamental Understanding of Technologies for Ultra Reduced Emission Vehicles) | |
| Status | Completed | |
| Energy Categories | Energy Efficiency(Transport) 50%; Other Power and Storage Technologies(Electric power conversion) 20%; Other Power and Storage Technologies(Energy storage) 30%; |
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| Research Types | Basic and strategic applied research 100% | |
| Science and Technology Fields | ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 75%; ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 25%; |
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| UKERC Cross Cutting Characterisation | Systems Analysis related to energy R&D (Other Systems Analysis) 40%; Not Cross-cutting 60%; |
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| Principal Investigator |
Professor R Thring No email address given Aeronautical and Automotive Engineering Loughborough University |
|
| Award Type | Standard | |
| Funding Source | EPSRC | |
| Start Date | 01 December 2011 | |
| End Date | 31 May 2016 | |
| Duration | 54 months | |
| Total Grant Value | £3,012,029 | |
| Industrial Sectors | Transport Systems and Vehicles | |
| Region | East Midlands | |
| Programme | User Led Skills and Knowledge Flow, User-Led Research | |
| Investigators | Principal Investigator | Professor R Thring , Aeronautical and Automotive Engineering, Loughborough University (99.986%) |
| Other Investigator | Dr R (Ricardo ) Martinez-Botas , Department of Mechanical Engineering, Imperial College London (0.001%) Dr M (Malcolm ) McCulloch , Engineering Science, University of Oxford (0.001%) Dr D (David ) Howey , Engineering Science, University of Oxford (0.001%) Dr DA Stone , Electronic and Electrical Engineering, University of Sheffield (0.001%) Professor NP (Nigel ) Brandon , Earth Science and Engineering, Imperial College London (0.001%) Dr GJ Offer , Earth Science and Engineering, Imperial College London (0.001%) Dr T Larkowski , Engineering and Computing, Coventry University (0.001%) Professor KJ Burnham , Engineering and Computing, Coventry University (0.001%) Dr M Sumislawska , Engineering and Computing, Coventry University (0.001%) Dr Q (Qing-Chang ) Zhong , Automatic Control and Systems Engineering, University of Sheffield (0.001%) Dr J (James ) Marco , School of Engineering, Cranfield University (0.001%) Dr F Assadian , School of Engineering, Cranfield University (0.001%) Dr S Longo , School of Engineering, Cranfield University (0.001%) Dr D J Auger , School of Engineering, Cranfield University (0.001%) |
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| Industrial Collaborator | Project Contact , Intelligent Energy (0.000%) Project Contact , Jaguar Land Rover Limited (0.000%) Project Contact , Lotus Engineering (0.000%) Project Contact , HORIBA MIRA Ltd (0.000%) Project Contact , Cenex (0.000%) Project Contact , AG Holding Ltd (trading as Axeon) (0.000%) Project Contact , Dennis Eagle Ltd (0.000%) Project Contact , SAIC Motor UK Technical Centre Ltd (0.000%) Project Contact , AVL Powertrain UK Ltd (0.000%) Project Contact , TUV Rheinland Mobility, Inc., USA (0.000%) |
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| Web Site | ||
| Objectives | ||
| Abstract | Hybrid electric vehicles (HEV) are far more complex than conventional vehicles. There are numerous challenges facing the engineer to optimise the design and choice of system components as well as their control systems. At the component level there is a need to obtain a better understanding of the basic science/physics of new subsystems together with issues of their interconnectivity and overall performance at the system level. The notion of purpose driven models requires models of differing levels of fidelity, e.g. control, diagnostics and prognostics. Whatever the objective of these models, they will differ from detailed models which will provide a greater insight and understanding at the component level. Thus there is a need to develop a systematic approach resulting in a set of guidelines and tools which will be of immense value to the design engineer in terms of best practice.The Fundamental Understanding of Technologies for Ultra Reduced Emission Vehicles (FUTURE) consortium will address the above need for developing tools and methodologies. A systematic and unified approach towards component level modelling will be developed, underpinned by a better understanding of the fundamental science of the essential components of a FUTURE hybrid electrical vehicle. The essential components will include both energy storage devices (fuel cells, batteries and ultra-capacitors) and energy conversion devices (electrical machine drives and power electronics). Detailed mathematical models will be validated against experimental data over their full range of operation, including the extreme limits of performance. Reduced order lumped parameter models are then to be derived and verified against these validated models, with the level of fidelity being defined by the purpose for which the model is to be employed.The work will be carried out via three inter-linked work packages, each having two sub-work packages. WP1 will address the detailed component modelling for the energy storage devices, WP2 will address the detailed component modelling for the energy conversion devices and WP3 will address reduced order modelling and control optimisation. The tasks will be carried out iteratively from initial component level models from WP1 and WP2 to WP3, subsequent reduced order models developed and verified against initial models, and banks of linear-time invariant models developed for piecewise control optimisation. Additionally, models of higher fidelity are to be obtained for the purpose of on-line diagnosis. The higher fidelity models will be able to capture the transient conditions which may contain information on the known failure modes. In addition to optimising the utility of healthy components in their normal operating ranges, to ensure maximum efficiency and reduced costs, further optimisation, particularly at the limits of performance where component stress applied in a controlled manner is considered to be potentially beneficial, the impact of ageing and degradation is to be assessed. Methodologies for prognostics developed in other industry sectors, e.g. aerospace, nuclear, will be reviewed for potential application and/or tailoring for purpose. Models for continuous component monitoring for the purpose of prognosis will differ from those for control and diagnosis, and it is envisaged that other non-parametric feature-based models and techniques for quantification of component life linked to particular use-case scenarios will be required to be derived. All members of the consortia have specific individual roles as well as cross-discipline roles and interconnected collaborative activities. The multi-disciplinary nature of the proposed team will ensure that the outputs and outcomes of this consortia working in close collaboration with an Industrial Advisory Committee will deliver research solutions to the HEV issues identified | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 30/01/12 | |
