Optimal Electric Vehicle Energy Efficiency & Recovery in an Intelligent Transportation System

Abstract

The limited range of Electric Vehicles can be significantly improved by means of optimal operation or control strategies enhanced with off-board data, provided by an Intelligent Transportation System, in addition to on-board information. The development of such strategies, for a twin axle Electric Vehicle, is the key goal of the OpEneR (Optimal Energy efficiency and Recovery) project. Within OpEneR, a highly advanced and beyond state-of-the-art MiL/SiL tool-chain has been developed, which enables the accurate development and validation of advanced energy management and safety strategies. Here a detailed model of the electrified vehicle powertrain equipped with an advanced regenerative braking system, is extended to includes a wide range of on-board and off-board sensors (GPS navigation, car-to-infrastructure, car-to-car data, etc.), the 3D real world driving route, as well as complex traffic and environmental conditions for the driver to interact with. The paper summarizes the design of the simulation tool-chain used to virtually develop the advanced strategies, for optimization of the torque distribution between the two electric-drive axles, energy-optimal route planning and short term traffic maneuvers. Preliminary simulation results obtained under several traffic scenarios are presented in this paper.