Developing FUTURE Vehicles (Fundamental Understanding of Technologies for Ultra Reduced Emission Vehicles)
Lead Research Organisation:
Loughborough University
Department Name: Aeronautical and Automotive Engineering
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.
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.
Planned Impact
As this proposal addresses the long term issues of the deployment of new types of technology into road vehicles, the whole of the UK road transport sector will benefit from this work. The impacts are wide-ranging, from a step change in the understanding of how key components age through to the development of methodologies that enable the extension of the life of the vehicle while minimising the cost.
There are a number of possible ways of meeting our future CO2 emissions reduction targets in the road transport sector, including advanced technology internal combustion engines, hybrids, and fuel cells. Battery electric propulsion will certainly play a significant role in decarbonising the transport sector (as well as assisting electricity grids with high penetrations of renewable generators) however, with present day technology, electric power is restricted to lightweight, short-range (urban) vehicles. Heavier and/or long-range vehicles will require hybrid low carbon technology. Most of the above scenarios involve the use of power electronics, electrical machines, batteries, capacitors and fuel cells. There is a need for a better fundamental understanding of the science involved in all of these devices, especially as used in vehicles.
This program will advance the understanding and control of these key components, especially the long term effects. This understanding will be captured in a codified set of open models, that will be accessible to all via an open website.
The short term beneficiaries of FUTURE Vehicles research will be other teams working in similar areas of technology; industrial development groups like those at Exide and Rayovac, SAFT and Maxwell, Qinetiq, Morgan, Intelligent Energy, AVL, Ricardo and Zytek. Long term beneficiaries include industrial production groups like those at JLR, Ford, General Motors, Nissan, Honda, Toyota and Lotus, policy makers, such as the DfT and DECC and ultimately the general public who will use vehicles that do not depend on imported petroleum, and do not emit carbon dioxide. In addition, many industrial technology development groups will find the results useful since the proposed work will add important information about new hardware that can be modelled in their simulation work. This will help ensure that the life time cost of the these components becomes more attractive, thus helping to displace the existing high carbon solutions.
Much of policy relies on the ability to predict how technology evolves and diffuses within a society. This relies on having reliable models of the systems. Therefore the work undertaken here will have a direct impact on the understanding of the efficacy and life expectation of advanced low carbon vehicles.
More widely, the results will also be useful to manufacturers of prototype vehicles who are currently restricted by limited understanding of science of these devices. Industrial production groups will benefit in the longer term since they will have the technology to put into the design of their production vehicles.
There are a number of possible ways of meeting our future CO2 emissions reduction targets in the road transport sector, including advanced technology internal combustion engines, hybrids, and fuel cells. Battery electric propulsion will certainly play a significant role in decarbonising the transport sector (as well as assisting electricity grids with high penetrations of renewable generators) however, with present day technology, electric power is restricted to lightweight, short-range (urban) vehicles. Heavier and/or long-range vehicles will require hybrid low carbon technology. Most of the above scenarios involve the use of power electronics, electrical machines, batteries, capacitors and fuel cells. There is a need for a better fundamental understanding of the science involved in all of these devices, especially as used in vehicles.
This program will advance the understanding and control of these key components, especially the long term effects. This understanding will be captured in a codified set of open models, that will be accessible to all via an open website.
The short term beneficiaries of FUTURE Vehicles research will be other teams working in similar areas of technology; industrial development groups like those at Exide and Rayovac, SAFT and Maxwell, Qinetiq, Morgan, Intelligent Energy, AVL, Ricardo and Zytek. Long term beneficiaries include industrial production groups like those at JLR, Ford, General Motors, Nissan, Honda, Toyota and Lotus, policy makers, such as the DfT and DECC and ultimately the general public who will use vehicles that do not depend on imported petroleum, and do not emit carbon dioxide. In addition, many industrial technology development groups will find the results useful since the proposed work will add important information about new hardware that can be modelled in their simulation work. This will help ensure that the life time cost of the these components becomes more attractive, thus helping to displace the existing high carbon solutions.
Much of policy relies on the ability to predict how technology evolves and diffuses within a society. This relies on having reliable models of the systems. Therefore the work undertaken here will have a direct impact on the understanding of the efficacy and life expectation of advanced low carbon vehicles.
More widely, the results will also be useful to manufacturers of prototype vehicles who are currently restricted by limited understanding of science of these devices. Industrial production groups will benefit in the longer term since they will have the technology to put into the design of their production vehicles.
Organisations
- Loughborough University (Lead Research Organisation)
- Proton (United Kingdom) (Project Partner)
- Cenex (United Kingdom) (Project Partner)
- TUV North Mobility (Project Partner)
- Axeon Ltd (Project Partner)
- MIRA (United Kingdom) (Project Partner)
- Anstalt für Verbrennungskraftmaschinen List (Project Partner)
- Dennis Eagle Ltd (Project Partner)
- Intelligent Energy (United Kingdom) (Project Partner)
- SAIC Motor (United Kingdom) (Project Partner)
- Tata Motors (United Kingdom) (Project Partner)
Publications
Aizad T
(2014)
Advances in Systems Science
Al-Jazaeri A
(2014)
Fuzzy Logic Control for energy saving in Autonomous Electric Vehicles
Antaloae C
(2012)
A Novel Method for the Parameterization of a Li-Ion Cell Model for EV/HEV Control Applications
in IEEE Transactions on Vehicular Technology
Cai J
(2014)
A compact power converter for hybrid energy systems
Cao X
(2018)
Multilayer Modular Balancing Strategy for Individual Cells in a Battery Pack
in IEEE Transactions on Energy Conversion
Cao X
(2015)
Ripple Eliminator to Smooth DC-Bus Voltage and Reduce the Total Capacitance Required
in IEEE Transactions on Industrial Electronics
Feig P
(2014)
Sensors-models trade-offs in battery state estimation
Fly A
(2015)
Temperature regulation in an evaporatively cooled proton exchange membrane fuel cell stack
in International Journal of Hydrogen Energy
Fotouhi A
(2017)
Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies
in IET Power Electronics
Fotouhi A
(2018)
Accuracy Versus Simplicity in Online Battery Model Identification
in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Fotouhi A
(2016)
A review on electric vehicle battery modelling: From Lithium-ion toward Lithium-Sulphur
in Renewable and Sustainable Energy Reviews
Ganesh, M
(2012)
Influence of Cost Function on EV Powertrain Sizing
Gregory Offer (Contributor)
(2013)
Welcome to the Car of the FUTURE
Gyftakis K
(2015)
Dielectric Characteristics of Electric Vehicle Traction Motor Winding Insulation under Thermal Ageing
in IEEE Transactions on Industry Applications
Gyftakis K
(2015)
Comparative Experimental Investigation of the Broken Bar Fault Detectability in Induction Motors
in IEEE Transactions on Industry Applications
Hu X
(2015)
Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling
in IEEE Transactions on Industrial Electronics
J. Auger D
(2014)
Impact of Battery Ageing on an Electric Vehicle Powertrain Optimisation
in Journal of Sustainable Development of Energy, Water and Environment Systems
Kim J
(2015)
Power Spectrum-Based Detection of Induction Motor Rotor Faults for Immunity to False Alarms
in IEEE Transactions on Energy Conversion
Kong H
(2015)
Cooperative Distributed Model Predictive Control via Linear Programming?A Divide and Conquer Approach**This work was supported by the "Developing FUTURE Vehicles" project of the Engineering and Physical Sciences Research Council under the UK Low Carbon Vehicles Integrated Delivery Programme.
in IFAC-PapersOnLine
Longo S
(2014)
Mechatronics in Sustainable Mobility: Two Electric Vehicle Applications
in The Journal of Sustainable Mobility
McCarthy N
(2016)
PTFE mapping in gas diffusion media for PEMFCs using fluorescence microscopy
in International Journal of Hydrogen Energy
Merla Y
(2016)
Novel application of differential thermal voltammetry as an in-depth state-of-health diagnosis method for lithium-ion batteries
in Journal of Power Sources
Mohan G
(2013)
An Optimization Framework for Comparative Analysis of Multiple Vehicle Powertrains
in Energies
Offer G
(2012)
Module design and fault diagnosis in electric vehicle batteries
in Journal of Power Sources
Offer, G , J
Future of transport in 20 years
Papazoglou A
(2014)
Nonlinear Filtering Techniques Comparison for Battery State Estimation
in Journal of Sustainable Development of Energy, Water and Environment Systems
Papazoglou, A
(2013)
Computational Aspects of Estimation Algorithms for Battery-Management Systems
Qing-Chang Zhong
(2013)
Improving the Power Quality of Traction Power Systems with a Single-Feeding Wire
| Description | Key findings have been produced in the form of the application of batteries to vehicles, specifically to do with module design and fault diagnosis, parameterisation of Li-Ion cells for control purposes, a comparative analysis of multiple vehicle powertrains, uneven heat generation in vehicle power packs and the effect of the resulting thermal gradients, and combined impedance and surface temperature measurement Also the impact of battery aging on electric vehicle performance, and a ripple eliminator for smoothing DC bus voltage. |
| Exploitation Route | These findings will probably be used by the manufacuters of present and future electric vehicles, such as Jaguar Land Rover, and their suppliers, such as Horiba-MIRA, Johnson-Matthey Batteries and Intelligent Energy. |
| Sectors | Electronics,Environment,Transport |
| URL | http://www.futurevehicles.ac.uk/ |
| Description | The results of the research are being used by Jaguar Land Rover, Horiba-MIRA, Cobham and Intelligent Energy. These companies are making use of the outputs in terms of batteries, fuel cells, electrical machines, solid state electronics, control systems and reduced order modelling. The project has helped contribute towards the establishment of two new battery systems engineering groups (Dr Gregory Offer @ Imperial College London, and Dr David Howey @ Oxford University) and a new battery control group (Dr Daniel Augur @ Cranfield University) in the UK, and helped lay the foundation and contributed towards the eco-system of low carbon vehicle technology research in the UK which eventually led to the foundation of the Faraday Institution (CoIs on EP/S003053/1, Gregory Offer, Billy Wu). |
| First Year Of Impact | 2011 |
| Sector | Energy,Environment,Transport |
| Impact Types | Economic |
| Description | Faraday Challenge: Innovation - research and development |
| Amount | £6,866,040 (GBP) |
| Funding ID | TS/R013780/1 |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2018 |
| End | 07/2021 |
| Description | H2020-NMBP-ST-IND-2018-2020 (Industrial Sustainability) |
| Amount | € 7,920,588 (EUR) |
| Funding ID | 8144471 |
| Organisation | European Commission H2020 |
| Sector | Public |
| Country | Belgium |
| Start | 01/2019 |
| End | 07/2022 |
| Description | Reconfigurable test rig for electric vehicle powertrain optimization |
| Amount | £56,000 (GBP) |
| Funding ID | EP/K503927/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2015 |
| End | 09/2015 |
| Description | Revolutionary Electric Vehicle Battery (REVB) |
| Amount | £827,503 (GBP) |
| Funding ID | EP/L505298/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2014 |
| End | 05/2017 |
| Description | Revolutionary Electric Vehicle Battery (REVB) - design and integration of novel state estimation/control algorithms & system optimisation technique |
| Amount | £468,617 (GBP) |
| Funding ID | EP/L505286/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2014 |
| End | 04/2017 |
| Title | PTFE Mapping In Gas Diffusion Media For PEMFCs Using Fluorescence Microscopy dataset |
| Description | Original images and polarisation data related to the article "PTFE Mapping In Gas Diffusion Media For PEMFCs Using Fluorescence" published in International Journal of Hydrogen Energy |
| Type Of Material | Database/Collection of data |
| Year Produced | 2016 |
| Provided To Others? | Yes |
| URL | https://repository.lboro.ac.uk/articles/dataset/PTFE_Mapping_In_Gas_Diffusion_Media_For_PEMFCs_Using... |
| Title | PTFE Mapping In Gas Diffusion Media For PEMFCs Using Fluorescence Microscopy dataset |
| Description | Original images and polarisation data related to the article "PTFE Mapping In Gas Diffusion Media For PEMFCs Using Fluorescence" published in International Journal of Hydrogen Energy |
| Type Of Material | Database/Collection of data |
| Year Produced | 2016 |
| Provided To Others? | Yes |
| URL | https://repository.lboro.ac.uk/articles/dataset/PTFE_Mapping_In_Gas_Diffusion_Media_For_PEMFCs_Using... |
| Title | BATTERY MODEL COMPRISING PLURALITY OF EQUIVALENT CIRCUIT NETWORKS AND INTERFACE ELEMENT COUPLING THEM |
| Description | The disclosure provides a method and apparatus for determining a characteristic of a battery within a system. The method comprises: defining a model comprising a plurality of equivalent circuit networks and an interface element through which the equivalent circuit networks are coupled; monitoring at least one observable parameter of the system; and calculating a battery characteristic based on the observable parameter and the model. |
| IP Reference | WO2016151336 |
| Protection | Patent application published |
| Year Protection Granted | 2016 |
| Licensed | No |
| Impact | The model is being further developed, and is likely to support a commercial business model providing parameterised battery models for industry. |
| Description | Advanced Battery Power Conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Dr Gregory Offer gave a presentation at Advanced Battery Power Conference, giving an overview of our work on lithium ion batteries, including research done as part of the FUTURE vehicle project. |
| Year(s) Of Engagement Activity | 2016 |
| Description | JLR Catapult Energy Storage Conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | Dr Gregory Offer gave an invited talk giving an overview on our work on lithium ion batteries, to an audience principally from JLR. |
| Year(s) Of Engagement Activity | 2016 |
| Description | Low Carbon Vehicle Event 2012 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Primary Audience | Professional Practitioners |
| Results and Impact | Invited to talk about the FUTURE Vehicle Project. |
| Year(s) Of Engagement Activity | 2012 |
| Description | Low Carbon Vehicle Partnership Innovation Working Group |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Primary Audience | Professional Practitioners |
| Results and Impact | As one of the board members of the group, I gave a presentation about the FUTURE Vehicles Project. |
| Year(s) Of Engagement Activity | 2013 |
| Description | Resource 2012 |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Primary Audience | |
| Results and Impact | Displaying research at Resource 2012, Oxford University. |
| Year(s) Of Engagement Activity | 2012 |