Energy Efficient Lateral Motion Control for Future Electric Vehicles
Examensarbete för masterexamen
Systems, control and mechatronics (MPSYS), MSc
Abstract The automotive industry is facing one of its most exciting technological turning points. On one hand, manufacturers are electrifying their fleets driven by environmental concerns, regulation, and economic incentives. On the other hand, future electric vehicles (EV) are expected to exploit various sensors concerning environment perception and vehicle motion sensing, as well as different actuator configurations, where even more control degree of freedom is added due to the advent of autonomous driving. Nevertheless, EVs still suffer from a major limitation when compared with internal combustion vehicles: the energy density, and consequently the driving range. The integration of autonomous capabilities in EVs, coupled with the need for energy-efficient vehicle motion control, suggest energy-optimal trajectory planning as a promising technology to address this challenge. While energy-efficient longitudinal control technologies such as ECO-cruise control are already mature and widely implemented, the combination of lateral and longitudinal control is still an active area of research. In this thesis, nonlinear and economic model predictive control is applied to minimize the energy consumption of an EV given a reference path and longitudinal velocity profile. The focus of the research is on achieving efficient, robust, and real-time computational performance. To this end, the vehicle model is simplified, and the testing conditions are constrained to low acceleration limits. High-fidelity vehicle simulations using the IPG CarMaker software are conducted on a test track. The re lation between lateral and longitudinal control and savings in energy consumption is explored, in order to conclude on what is the energy consumption reduction potential from the control perspective. In specific, the displacement from path’s center line and the reference longitudinal velocity are examined individually and in combination to determine their influence on energy savings. Results show that, for limited accelerations, the greatest potential lie on optimizing longitudinal control, where significant energy savings can be attained at the expense of limited decrease in average longitudinal velocity. However, the intricate trade-off between the economic cost, the energy consumption, and the reference tracking cost in the MPC formulation led to limited energy savings when moving from path tracking to trajectory planning.