Energy-Optimal Regenerative Braking Strategy for Connected and Autonomous Electrified Vehicles: A Practical Design and Implementation for Real-World Commercial PHEVs

This paper presents an automated vehicle speed planning system called the energy-optimal deceleration planning system (EDPS), which aims to maximize energy-recuperation of regenerative braking on connected and autonomous electrified vehicles. Based on the impending deceleration requirements resulting from speed reduction ahead of turning or stopping at a nearby intersection, a recuperation-energy-optimal speed profile is computed by maximizing the regenerative braking energy-efficiency while satisfying the physical limits of an electrified powertrain. Optimal deceleration commands are determined by a parameterized polynomial-based deceleration model that is obtained by regression analyses with real-world test data from human drivers. For the fast-tracking validation, the proposed speed planning algorithm is compared with human drivers and we show that EDPS-based autonomous driving results in improved energy recuperation and a shorter driving time.