Driving mode shift strategy for an electric heavy truck to minimize the energy consumption and shift frequency

Jun Guo, Jinglai Wu, Yunqing Zhang and Yayun Peng

Energy, 2025, vol. 319, issue C

Abstract: The electrification of commercial vehicles, especially heavy trucks, is important for reducing carbon emissions from delivery transportation. This study investigates the driving mode shift strategy in a two-axle driving electric heavy truck with 11 distinct driving modes. To select the optimal driving mode in real-time and to distribute the power torque appropriately to optimize the performance of the vehicle, a real-time equivalent energy minimization shift strategy considering the minimization of energy consumption and shift frequency is proposed in this paper. To be specific, the strategy first analyzes the power consumption of different driving modes at various velocities and then adopts a new scheme to limit the shift interval and considers the energy loss during gear shifting, with a focus on kinetic energy loss. A novel dynamic programming (DP) method that considers the shift interval is designed to derive the theoretically optimal solution. Furthermore, the hardware-in-the-loop (HIL) test and simulation results demonstrate that the proposed driving mode shift strategy not only can significantly reduce the transmission shift frequency but also does not depend on future driving conditions and yields a solution closely aligned with the DP method, which provides a solid foundation for further on-vehicle applications.

Keywords: Electric heavy truck; Multi-motor powertrain; Driving mode shift; Shift interval; Hardware-in-the-loop (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:319:y:2025:i:c:s0360544225006401

DOI: 10.1016/j.energy.2025.134998

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