Optimisation of Speed Trajectories to Improve the Energy Economy of Electric Vehicles
T. Goyal (TU Delft - Mechanical Engineering)
L Ferranti – Mentor (TU Delft - Learning & Autonomous Control)
Mauro Salazar Villalon – Mentor (Eindhoven University of Technology)
Thijs van Keulen – Mentor (Eindhoven University of Technology)
Barys Shyrokau – Coach (TU Delft - Intelligent Vehicles)
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Abstract
Electric vehicles are a cleaner and more efficient means of transport. However, the sub-energy-optimal acceleration and deceleration inputs of drivers result in speed trajectories that cause superfluous expenditure of the stored electrical energy in battery. Optimising the speed trajectories to minimise the consumption of stored energy is a potential strategy for the efficient operation of electric vehicles. In this thesis, we propose a numerical solution to the eco-driving problem by optimising the speed trajectories via Pontryagin’s Minimum Principle. The solution is robust to the vehicle parameters and the driving conditions, and is used to generate energy-aware driving advice for near-straight line driving manoeuvres. In the end, we test the global optimality of the speed trajectories by convexification of the problem.