Dr Daniel Gladwin

Staff Photo

Contact Details

d.gladwin@sheffield.ac.uk

Tel: +44 (0)114 22 25849

ORCID: 0000-0001-7195-5435

Qualifications

  • PhD, University of Sheffield
  • MEng (Electronic Engineering - Computer Architecture), University of Sheffield 2004

Research Activities

  • Control-power systems
  • Power electronics
  • Embedded systems
  • Energy storage and management
  • Intelligent systems
  • Telematics
  • Optimisation and modelling
  • Evolutionary computing

Additional Research Interests

  • Robotics
  • IoT / Industry 4.0 / Security

Responsibilities

  • Senior Lecturer
Profile

I received my M.Eng. and Ph.D. degrees in Electronic Engineering from the University of Sheffield, in 2004 and 2009, respectively. I undertook postdoctoral positions from 2009 to 2010 in power electronics and safety critical embedded systems for electric vehicles. In 2012 I became a lecturer in the Department of Electronic and Electrical engineering as a member of the Electrical Machines and Drives research group. I am currently a Senior Lecturer in Electrical Energy Storage and Intelligent Systems.

My primary research is focused on electrical energy storage across a wide range of applications that includes automotive, power grid, aerospace, rail, and consumer mobile. I focus on energy storage technologies such as batteries, super capacitors and flywheels and how the different characteristics of each technology can be exploited to meet the requirements of the application, either individually or as a combined solution. I investigate the whole system from the low level storage components and its behaviour right through to the power electronics and interface to the source or load.

I am particularly interested into the diagnostics and prognostics of energy storage technology for high power applications. For batteries this means developing algorithms to diagnose accurately the state of charge, health and power of cells at anytime whether in use or not. Moreover, my latest work involves predicting the behaviour of battery cells based upon a set of given future operating conditions. This is a very important research field to industry as it allows decisions to be made on system sizing, topology and leads to informed decisions on the operation of the battery systems, for example to maximise revenue for providing services whilst minimising degradation. Interestingly, this work allows me to make use of my other research interests in optimisation and intelligent systems. My PhD research developed a novel methodology for the successful synthesis, through the use of genetic programming, of controllers for non-linear and time delayed systems. To support the search methodology, a software framework was developed that facilitates parallel and distributed computations to solve for a multi-objective optimisation.

I am Deputy Director of the Centre for Research into Electrical Energy Storage and its Applications (CREESA). I lead the work on electrochemical energy storage for grid scale storage and manage the the UKs only research-led large scale energy storage test facility with 1200sqm of land and an 11kV connection with capacity of 4.1MW. The flagship project on the site is a £3.8M lithium titanate 2MW / 1MWh grid connected energy storage demonstrator, built and commissioned by the CREESA team in 2015. CREESA hosts numerous projects across different applications including a EPSRC funded £1.5M TransEnergy project that is investigating the feasibility of storage on different types of railway networks and in particular the integration of parked electric vehicles close to lines. Furthermore, I am currently leading a H2020 project to install Europe’s largest hybrid flywheel battery energy storage system that comprises 4 x 250kW novel flywheels.

Research Projects

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Research Students

Student Degree Status Primary/Secondary
Nejad S PhD Graduated Primary
Smith MJ PhD Graduated Primary
Zhao R PhD Graduated Primary
Duke A PhD Graduated Secondary
Pan Q PhD Graduated Secondary
Pothi N PhD Graduated Secondary
Shi J PhD Graduated Secondary