Abstract:

Optimising energy autonomy for autonomous electric vehicles is a significant challenge in sustainable and environmentally friendly mobility. To this end, the authors propose a novel double-layer control architecture designed to drive the longitudinal motion of electric vehicles equipped with a regenerative braking system. The first layer resembles an Adaptive Cruise Control, while the second one is enabled during the braking phase and is devoted to the blending between the motor torque and the hydraulic one. This layer is synthesised as a Nonlinear Model Predictive Control strategy so as to maximise the efficiency of the regenerative system. The control architecture, by combining the two control strategies, allows to reduce the overall energy consumption for electric vehicles, while simultaneously ensuring a safer, more sustainable, and comfortable driving experience. Additionally, this combination is capable of compensating for any efficiency issues arising from external factors, such as different traffic conditions encountered by the vehicle. Utilising the MiTraS virtual testing platform, a thorough simulation study was done while taking into account two actual driving scenarios to determine the efficacy of the proposed control architecture. Results support the suggested control architecture's safety and robustness in ensuring the tracking of the intended trajectory while minimising energy usage.