Research Fellow, Energy Research Institute
NTU Main Campus, Singapore
The Energy Research Institute at NTU (ERIAN) invites applications for the position of Research Fellow (RF) to study the characteristic of electric vehicles and the related energy management systems. The RF is expected to work on the challenges involved in coordinating heterogeneous sensor modules and establishing communication and data acquisition for thermal data collection inside the electric vehicle. The tasks include the modelling of the electric vehicle in a simulation platform that will characterize the vehicle energy performance based on the real time driving data from the sensor network. Elaborate model of the vehicle energy storage system and health monitoring needs to be carried out.
The successful candidate will work in a vibrant environment with state-of-the-art laboratory and with a team of multi-disciplinary researchers and scientists. Candidates with strong knowledge and working experience on analogue experiments of energy storage system and thermal modelling are desired.
- Work to characterize the energy management system of electric vehicles based on real time data.
- Work on developing simulation model that represents the electric vehicle and vehicle energy storage system that can reproduce all the vehicle events.
- Data collection using data acquisition tools, data collation and analysis.
- Data modelling for the real time driving scenarios and validation of the vehicle simulation model using the driving data.
- Working knowledge on Robotic Operating Systems (ROS) is desired.
- PhD in Mechanical or Electrical Engineering with background in energy storage management and thermal modeling.
- Strong technical skills in thermal modeling and battery characterization.
- Deep knowledge and working experience in the use of MATLAB and other simulation tools such as Simulink, AmeSIM, and ANSYS, FLUENT or other related software.
- Experience in data collection using DAQ tools, data analytics and data modelling.
- Experience in handling electric vehicle diagnostics and sensor installation.
- Knowledge on vehicle CAN, OBD and ROS is desired.
- Working experience in scripting tools like R, Python or m-scripts is an advantage.
- Ability to work effectively with a diverse population.