Predicting Technology Development for Next Generation Clean Energy Systems

2022-2023 Fall
Faculty Department of Project Supervisor: 
Faculty of Engineering and Natural Sciences
Number of Students: 

The prediction of cost and efficiency of emerging energy technologies is an important task as it affects the investment decisions (for example, one can wait to transition to an alternative that is expensive now, but will be cheaper in the future). There are widely used methods, e.g. Moore’s Law and Wright’s Law, to predict the technology developments. In this project we would like to investigate these methods to predict technology developments of next generation clean vehicles and energy technologies. For this purpose in this project we aim to follow the following steps:

  • Determine next generation clean vehicle and energy technologies options. What are some alternative technologies/systems that can be used to for clean energy and mobility transition (e.g.  solar energy technologies, electric vehicles, hydrogen vehicles, etc.)?
  • Through literature survey, find data related to the cost and efficiency improvements of these technologies over the years. 
  • Use this data and above mentioned methods to obtain future cost and efficiency development scenarios for these technologies. Compare the methods in terms of their outcomes. 

The project is suitable for junior and senior level students. 

Related Areas of Project: 
Computer Science and Engineering
Electronics Engineering
Materials Science ve Nano Engineering
Mechatronics Engineering
Industrial Engineering

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