Co-optimization of Energy Efficiency and Drivability for Dual-Motor Electric Commercial Vehicles: A Topology-Aware Hierarchical Approach

Dual-motor architectures provide additional operating degrees of freedom for electric commercial vehicles (ECVs), but the integration of automated manual transmissions (AMTs) introduces torque discontinuities during gear-related mode transitions. Existing energy management strategies usually focus on steady-state efficiency optimization, while the mechanical feasibility of mode transitions is often considered separately or neglected. To address this issue, this study proposes a topology-aware hierarchical control framework for dual-motor ECVs. The framework combines an offline global efficiency map with an online transition-feasibility arbitration mechanism. In the offline layer, the energy-oriented operating mode and torque split are extracted over the vehicle-speed and wheel-torque domain. In the online layer, a topology-based transition matrix is used to identify mechanically singular mode transitions, and potentially torque-interrupting commands are re-routed through feasible bridge modes. The proposed method embeds powertrain topology constraints into the real-time implementation of an offline optimal map, thereby complementing conventional global optimization methods with transition-feasibility arbitration. Simulation results under the CHTC driving cycle show that the proposed strategy improves torque continuity during mode transitions while retaining most of the energy-saving benefit of the unconstrained efficiency-oriented strategy. Compared with the rule-based strategy, the proposed method reduces SOC-equivalent energy consumption by 10.7%, and recovers 65.5% of the DP-achievable energy-saving potential. Hardware-in-the-Loop (HIL) results further demonstrate that the proposed online arbitration logic can be executed within the controller sampling period.