Efficient Eco-Driving Control for EV Platoons in Mixed Urban Traffic Scenarios Considering Regenerative Braking

Connected and automated vehicles provide enormous opportunities for improving fuel economy, safety and capacity of the transportation system. In this paper, an Eco-driving speed advisory for electric vehicle platoons is proposed by taking regenerative braking and braking torque distribution into account. An efficient Poly-Eco speed planning method is then presented to improve computational efficiency. A control scheme comprising a splitting/merging decision-making and a modified intelligent driver model vehicle-following controller is established to verify the effectiveness of the proposed Poly-Eco speed advisory in mixed traffic scenarios. Comprehensive hardware-in-the-loop tests are conducted to examine the proposed Poly-Eco control scheme in terms of energy consumption, traffic efficiency and ride comfort. The rule-based and sequential programming (SP) methods are used for comparison. The comparison results show that the proposed Poly-Eco method can reduce the energy consumption by 4.71% while guaranteeing lower jerk and less arrival time compared with the commonly-used SP method. The lapse time per period for the proposed Poly-Eco is only 2.3% of that for the SP method. In addition, the proposed Poly-Eco method stages superior performance under typical mix traffic scenarios.