TY - JOUR
T1 - MPC-based coordinated control for mode transition in power-split hybrid electric vehicles
T2 - Dynamic modeling, torque fluctuation suppression, and experiment
AU - Yan, Qi
AU - Liu, Hui
AU - Gao, Pu
AU - Yang, Dianzhao
AU - Jiao, Jiaxin
N1 - Publisher Copyright:
© 2026 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/
PY - 2026/12
Y1 - 2026/12
N2 - Among the various configurations of hybrid electric vehicles (HEVs), power-split HEVs typically achieve superior fuel economy by dynamically coordinating their operational modes to keep the engine operating within its optimal efficiency region across a wide range of driving conditions. However, for power-split HEVs, mode transition causes torque fluctuations and imptacts driving smoothness and drivetrain safety. To address this challenge, we propose a novel dynamic coordinated control strategy (DCCS) that integrates a staged control framework with model predictive control (MPC) to effectively suppress transient disturbances. First, a dynamic model of the power coupling mechanism is established to characterize the transition between electric vehicle (EV) mode and electric variable transmission (EVT) mode. Then, a multi-stage control scheme is designed to segment the engine start-stop process into distinct phases. Next, the MPC algorithm is further employed to formulate jerk minimization as a constrained optimization problem, enabling real-time coordination of motor torques to maintain near-constant output shaft acceleration. Finally, simulation results demonstrate that the proposed method significantly reduces both output torque fluctuations and maximum jerk compared to conventional control strategies. Bench experiments validate a 38.2 % reduction in engine start time with minimized vibration. This study introduces a novel approach to transient control in power-split HEVs, paving the way for significant improvements in vehicle operation smoothness.
AB - Among the various configurations of hybrid electric vehicles (HEVs), power-split HEVs typically achieve superior fuel economy by dynamically coordinating their operational modes to keep the engine operating within its optimal efficiency region across a wide range of driving conditions. However, for power-split HEVs, mode transition causes torque fluctuations and imptacts driving smoothness and drivetrain safety. To address this challenge, we propose a novel dynamic coordinated control strategy (DCCS) that integrates a staged control framework with model predictive control (MPC) to effectively suppress transient disturbances. First, a dynamic model of the power coupling mechanism is established to characterize the transition between electric vehicle (EV) mode and electric variable transmission (EVT) mode. Then, a multi-stage control scheme is designed to segment the engine start-stop process into distinct phases. Next, the MPC algorithm is further employed to formulate jerk minimization as a constrained optimization problem, enabling real-time coordination of motor torques to maintain near-constant output shaft acceleration. Finally, simulation results demonstrate that the proposed method significantly reduces both output torque fluctuations and maximum jerk compared to conventional control strategies. Bench experiments validate a 38.2 % reduction in engine start time with minimized vibration. This study introduces a novel approach to transient control in power-split HEVs, paving the way for significant improvements in vehicle operation smoothness.
KW - Dynamic coordinated control strategy
KW - Mode transition
KW - Model predictive control
KW - Power-split HEV
UR - https://www.scopus.com/pages/publications/105050399278
U2 - 10.1016/j.cjme.2025.100174
DO - 10.1016/j.cjme.2025.100174
M3 - Article
AN - SCOPUS:105050399278
SN - 1000-9345
VL - 39
JO - Chinese Journal of Mechanical Engineering (English Edition)
JF - Chinese Journal of Mechanical Engineering (English Edition)
M1 - 100174
ER -