Co-Optimized Analytical Solution of Speed Planning and Energy Management for Automated Hybrid Electric Vehicles Under Multisignal Intersections Scenario

Abstract

Eco-driving is a viable technology with higher energy-saving potential at signalized intersections. The rapid development of connected and automated technology provides more opportunities for the eco-driving of hybrid electric vehicles (HEVs). However, it is more challenging to co-optimize speed planning and energy management due to their coupling and complex features. To this end, a co-optimization method of speed planning and energy management under multisignal intersections scenario is proposed for automated HEV by obtaining an explicit optimal analytical solution. First, considering the shifting behavior of a parallel HEV, a single-parameter gear-shifting model is adopted. Then, the co-optimization method is proposed, which consists of two steps. In the first step, the vehicle arrival time at signalized intersections is determined by calculating a vehicle reference speed. In the second step, the speed and powertrain energy management are co-optimized using the Pontryagin minimum principle (PMP) by deriving an optimal analytical solution under multisignal intersections. Finally, an iterative loop algorithm is utilized to compute the initial co-states, and the sensitivity analysis is conducted in this sequel. Simulation results demonstrate that the proposed co-optimization approach can greatly reduce the computational cost while maintaining satisfactory energy efficiency as compared with the widely used dynamic programming (DP) method.