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Model Predictive Control Strategies for Electric Endurance Race Cars Accounting for Competitors Interactions
This paper presents model predictive control strategies for battery electric endurance race cars accounting for interactions with the competitors.
A Two-dimensional Spatial Optimization Framework for Vehicle Powertrain Systems
This paper presents a modeling framework to optimize the two-dimensional placement of powertrain elements inside the vehicle, explicitly accounting for the rotation, relative placement and alignment.
Maximum-distance Race Strategies for a Fully Electric Endurance Race Car
Thereby, the lower level computes the minimum-stint-time Powertrain Operation (PO) for a given battery energy budget and stint length, whilst the upper level leverages that information to jointly optimize the stint length, charge time and number of pit stops, in order to maximize the driven distance in the course of a fixed-time endurance race.
Minimum-lap-time Control Strategies for All-wheel Drive Electric Race Cars via Convex Optimization
This paper presents a convex optimization framework to compute the minimum-lap-time control strategies of all-wheel drive (AWD) battery electric race cars, accounting for the grip limitations of the individual tyres.
