About SVeCLab

Located in the Design Hub, room DCG.1C, within the Technology Park at Coventry University, the Smart Vehicles Control Lab (SVeCLab) is a recently established multi- and inter-disciplinary lab shared among the Vehicle Dynamics, Control Systems, and Low Carbon Vehicles themes within the Centre for Mobility and Transport at Coventry University.

While open to a wide spectrum of applications, the lab’s main motivation is in conducting research and supporting teaching involving Modelling, Control & Optimisation with emphasis on Hybrid Electric/Electric Vehicles and Connected & Autonomous Vehicles.

Founding Members

Dr Arash Moradinegade DIZQAH – Coventry University
Senior Lecturer in Intelligent Transport Systems

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Dr Mauro Sebastián INNOCENTE – Coventry University
Lecturer in Aerospace Engineering

Founding Member & Research Visitor

Dr José Martín HERREROS ARELLANO – University of Birmingham
Lecturer in Vehicle Engineering

Research Students

Brandon Lee BALLARD, PhD Student
Distributed Predictive Control Strategies for Active Suspension Systems with Preview
(Main Supervisor: Dr A.M. Dizqah)

Zihao Liu
Zihao LIU, PhD Student
Mission Dependent Predictive Engine and After-Treatment Control Strategies for Passenger Car Diesel Engines
(Main Supervisor: Dr A.M. Dizqah)

Paolo GRASSO, MSc student & Research Intern
Mathematical Modelling of Spread of Fire Underpinning Algorithmic Developments for Autonomous Swarms of Fire-Fighting Drones
(Main Supervisor: Dr M.S. Innocente)


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Real-Time Simulation platforms as an affordable test bed to:

  • Simulate HEV/EVs in signal level.
  • Develop real-time implementation of the control algorithms for autonomous vehicles and HEV/EVs on ECUs.
  • Simulate smart grid and microgrids for Vehicle-to-Grid (V2G) applications.
  • Integrating driver- and the signal-level hardware-in-the-loop simulators to develop and test advanced control strategies.

Mini-roller bench test rig to characterise planar robots.

Small robots as the affordable test bed to:

  • Develop Connected Vehicles control algorithms.
  • Develop Algorithms for autonomous vehicles.
  • Develop vehicle-to-grid algorithms.
  • Develop energy management strategies for EVs.

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