Optimising energy consumption on straight roads using regression analysis

University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

Author: Gabriel Masso; [2019]

Keywords: ;

Abstract: Cloud computation together with robotics has opened up possibilitiesto process large amount of data (big data) generated by the greatnumber of robotic systems. Todays vehicles are equipped withhundreds of sensors generating a lot of data that needs to beprocessed. The data can further be analysed and used to obtainmodels predicting the dynamics of the vehicles. It is thereforepossible to optimise the vehicle performance by studying thepredictive behaviour and finding the best combination of the vehicleparameters. In this thesis, the energy efficiency of an electric racingvehicle is studied on straight road whereafter an optimal velocityprofile is to be found. By using a multiple linear regression togetherwith regularization methods on previously recorded data, apredictive model managed to be obtained with an accuracy of 79.1 %.Having used this model in optimisation process, a velocity profilewas obtained which is shown that can enhance the efficiency of thesystem by 4.08%.

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