Bi-Level Optimization of Speed Trajectory and Power Management for Autonomous HEVs in Off-Road Scenarios

With the advent of intelligent and connected vehicle technology, the simultaneous optimization of speed trajectory and power management for autonomous hybrid electric vehicles (HEVs) has become a significant research hotspot to enhance energy efficiency further. Especially for off-road scenarios, restricted by complex road conditions, vehicle nonlinear dynamics, and different time scales between speed planning and power split optimization, finding these control variables in one optimal problem is quite challenging. Thus, this article proposes a bi-level optimal control strategy for autonomous HEV to reduce computational burden by separating simultaneous optimization into two subproblems. In the upper layer, a vehicle stability constraints system is designed with consideration of both external road characteristics and the vehicle's lateral stability to determine the longitudinal speed boundary to ensure the vehicle's driving safety in off-road scenarios. Then, speed planning is formulated as a MPC problem with time-varying constraints, and solved by roll optimization. In the bottom layer, an explicit MPC (EMPC) is developed to obtain explicit solutions to achieve real-time energy management. Finally, simulation results show that the proposed method decreases equivalent fuel by 4.06% compared with ECMS, significantly improving computational efficiency with a slight sacrifice on fuel economy, compared with MPC and DP.