2018-19

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Browsing 2018-19 by Author "Ajinkya Salunkhe"

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    Optimisation of Electronic Fuel Injector Using Machine Learning
    (2019-07-08T11:31:24Z) Vikram Asokan; Aditya Chebbi; Ajinkya Salunkhe; Shehzar Sheriff
    Current day statistics suggest that the rate of increase in consumption of existing non-renewable energy resources is exponential, which by no means is good news. As a result, humanity is moving towards an era of renewable energy resources such as hydropower, wind power and solar power. Through this move, we will be able to recognize more alternatives for power generation to sustain the lifespan on this planet and of this planet. The problem statement proposed in order to give life to this project, is the fact that our most easily exhaustible resource is extinguishing at an alarming rate, and not much can be done about it taking various factors into consideration. This project involves the idea of incorporating the latest Machine Learning concepts into the fuel injection process, so as to improvise on the process, its feedback, etc. This will facilitate for a better driving experience, a self-optimizing control unit and most importantly, efficient fuel usage. In addition to fuel conservation, the aim is to minimize the rubber band effect in high end automobiles with electronically controlled accelerators. The data obtained from reliable sources and equipment, with respect to concerned parameters will then be tabulated and performed an analysis upon, based on which we can progress with designing and training a Machine Learning model that optimises the process of electronic fuel injection.