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[{"model": "core.projectfund", "pk": 17919, "fields": {"project": 3003, "organisation": 2, "amount": 1003708, "start_date": "2017-09-30", "end_date": "2020-12-31", "raw_data": 19390}}]
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[{"model": "core.projectorganisation", "pk": 68126, "fields": {"project": 3003, "organisation": 582, "role": "PP_ORG"}}]
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[{"model": "core.projectorganisation", "pk": 68125, "fields": {"project": 3003, "organisation": 650, "role": "PP_ORG"}}]
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[{"model": "core.projectorganisation", "pk": 68124, "fields": {"project": 3003, "organisation": 330, "role": "PP_ORG"}}]
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[{"model": "core.projectorganisation", "pk": 68123, "fields": {"project": 3003, "organisation": 182, "role": "PP_ORG"}}]
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[{"model": "core.projectperson", "pk": 42148, "fields": {"project": 3003, "person": 3568, "role": "COI_PER"}}]
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| April 11, 2022, 3:46 a.m. |
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| April 11, 2022, 3:46 a.m. |
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[{"model": "core.projectperson", "pk": 42143, "fields": {"project": 3003, "person": 89, "role": "COI_PER"}}]
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| April 11, 2022, 3:46 a.m. |
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[{"model": "core.projectperson", "pk": 42142, "fields": {"project": 3003, "person": 1608, "role": "COI_PER"}}]
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| April 11, 2022, 3:46 a.m. |
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[{"model": "core.projectperson", "pk": 42141, "fields": {"project": 3003, "person": 92, "role": "PI_PER"}}]
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| April 11, 2022, 1:47 a.m. |
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{"title": ["", "ISCF Wave 1: Translational Energy Storage Diagnostics (TRENDs)"], "description": ["", "\nDegradation of lithium battery cells is a complex process occurring over multiple temporal and spatial domains. Improved understanding of cell health is a prerequisite for expanded use of Li-ion battery technology in many challenging applications. \n\nEarly detection of changes in critical parameters would enable performance assessment and degradation forecasting, as well as providing a route to predict the most likely eventual failure modes. Parameter detection requires the ability to measure a diverse set of static and dynamic properties that elucidate the state of a battery system. To enable efficient and safe battery operation, diagnostic schemes need to be fast, accurate, and reliable, work in near real-time, and detect potential faults as early as possible; to enable widespread practical adoption, parameter detection must be achieved with minimal added cost. \n\nIn tandem, the need to run accurate in-service battery models is critical, and would enable model-based control. Second only to safety monitoring of voltage and temperature, state-of-charge (SOC) estimation is the most important function of a battery management system (BMS). Better BMS SOC could help maximize battery performance and lifetime, but is often accurate to only +/- 10% - and simple methods to improve this accuracy do not currently exist. Models capable of predicting Li-ion performance under modest conditions are highly advanced. But significant progress is still needed to couple operational models suitable for the diagnosis and prognosis of degradation and failure with models of degradation mechanisms.\n\nGenerally faults and the resulting degradation manifest as capacity or power fade and often state-of-the-art techniques such as X-ray CT, open circuit voltage measurements, and thermal measurements are used to characterise the degradation. This proposal brings together a world-class team to address the critical issue of degradation and health estimation for leading lithium-ion-battery chemistries. We place particular focus on Translational Diagnostics, which we define as diagnostic methods that translate across length scales, across different domains, and across academic research into industry practice.\n\nKey outputs from our work will be a suite of new and validated diagnostic tools integrated with battery models for both leading and emerging lithium-ion and sodium- ion battery chemistries. We aim to ensure that these diagnostic tools are capable of cost-effective deployment on both small and large battery systems, and able to run in real time with sufficient accuracy and reliability, such that safer, more durable and lower cost electrochemical energy storage systems can be achieved\n\n"], "extra_text": ["", "\n\nPotential Impact:\nTRENDs will advance the state-of-the-art in battery diagnostic method, developing new methods that are cheap, quick and easy to deploy in the real world, and that relate to important indicators of battery health, and battery state of charge. In so doing TRENDs will continue to establish the UKs reputation as a centre of excellence in battery diagnostics and battery management. The project team are at the forefront of the UK's national capabilities in energy storage. WMG hosts the UK's High Value Manufacturing (HVM) Catapult in low carbon transport and is named as the electrical energy spoke of the Advanced Propulsion Centre (APC, a £1 billion 10-year commitment to the automotive industry) with which the consortium partners are already engaged. This is a recognised UK national strategic technology area within the automotive council with defined roadmaps for technology progression. Through our team members role in the energy storage for low carbon grids EPSRC challenge and capital projects, and Prof Brandons position as Co-Director of the SUPERGEN Energy Storage Hub, we are also strongly engaged in the application of lithium battery technology for grid scale energy storage, along with other electrochemical energy storage technologies such as sodium ion batteries and flow batteries. PS has strong links to UK national science facilities such as Diamond which will further reinforce the ability of these national facilities to contribute to this key area. The UKs national measurement facility, NPL, is a partner in this project, and recognises the impact of it on their capability to contribute to the UKs battery metrology capability. We also have strong engagement from a suite of other key industry partners, to ensure that our science enhances the UK industry base in this important field.\n\nOur research will feed into the UK national roadmap in energy storage innovation, which is a key task being undertaken by the SUPERGEN Energy Storage Hub, and the automotive technology roadmaps of the UK automotive council. These emerging roadmaps have the authority and buy-in of the key stakeholders in the UK, and thus our research has the potential to inform policy makers and industry effectively. This will also facilitate public understanding of energy storage research and technology, including safety, sustainability, cost and performance, and we will continue to engage in policy debates and public engagement activities. For example through the Energy Futures Lab at ICL, the Energy Institute at UCL and Oxford Energy at OU.\n\nWhilst the main activities of the project are scientific in nature, we aim for maximum industrial and commercial impact of innovations arising from this research, through our industrial partners in the UK and beyond. The consortium partners are already engaged with translational networks including the automotive council, the APC and HVM Catapult. Through this we have taken the knowledge generated in EPSRC projects into translational projects under InnovateUK and commercialisation projects under APC. Our strong relationship with industry is evidenced by letters of support from key players in the energy storage industry, who have collectively committed £552k of direct and in-kind support to this research programme, including the funding of two PhD studentships.\n\nBattery energy storage is a recognized strategic technology for many industry sectors and UK companies engaged in the field report difficulties in recruitment of suitable qualified and experienced staff. The research staff and students employed on and engaged with, this project will be exposed to the range of skills and disciplines necessary to contribute to academia and industry in this multi-disciplinary area. Our management plan recognizes the need to help develop these trained people, offering opportunities for exchange between partners, together with regular engagement and discussion with industry experts.\n\n\n"], "status": ["", "Closed"]}
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| April 11, 2022, 1:47 a.m. |
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{"external_links": [11704]}
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| April 11, 2022, 1:47 a.m. |
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[{"model": "core.project", "pk": 3003, "fields": {"owner": null, "is_locked": false, "coped_id": "4e874b86-9477-41b3-9ddb-881eafedb90c", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 19373, "created": "2022-04-11T01:35:28.063Z", "modified": "2022-04-11T01:35:28.063Z", "external_links": []}}]
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