View a selection of AME's key projects, organised by area of research.
The H1PERBAT project took an integrated approach to remove fundamental constraints on capacity, energy density and thermal management of EV batteries, and will realise a step change in system performance.
This project seeks to develop and test new processes that enable rapid, high-quality, low-cost manufacturing of prototype samples of e-motor lamination stacks.
Midlands Centre for Data Driven Metrology (MCDDM)
The Midlands Centre for Data-Driven Metrology (MCDDM) is a multi-site collaboration between the University of Nottingham, Loughborough University, and Coventry University.
InnEx developed a highly innovative lightweight exhaust system for forced induction diesel and petrol automotive vehicles.
REsilient Water Innovation for Smart Economy (REWAISE)
REWAISE will create a new “smart water ecosystem”, mobilising all relevant stakeholders to make society embrace the true value of water, reducing freshwater and energy use.
People-Centred Productivity (PCP)
AREA – Augmented Reality Enhanced Assembly
This explored the use of augmented reality in the context of manufacturing assembly workers required to conduct complex product assemblies (such as high performance battery packs for electric vehicles) with increased efficiency.
This is a unique multi-disciplinary project that will bring electrochemists, materials scientists and experts in electronic manufacturing processes together with creative and artistic designers to produce smart textiles and fabrics with the aim of revolutionising assistive technology (AT) for older people.
Niche Vehicle Network (Light Niche)
Aligning the scope of the competition by delivering weight reduction in the powertrain systems of road-going niche vehicles.
Ultrasonically Enabled Low Temperature Immersion and Electroless Metallisation (ULTIEMet)
Reducing the temperatures and process times of electroless and immersion plating processes using ultrasound.
Virtual Exhaust Prototyping System (VExPro)
VExPro aims to optimise the throughput of multi-disciplinary and multi-physics optimisation problems.