Abstract
This paper presents the modelling and calculations for a hybrid electric vehicle (HEV) in parallel configuration, including a main electrical driving motor (EM), an internal combustion engine (ICE), and a starter/generator motor. The modelling equations of the HEV include vehicle acceleration and jerk, so that simulations can investigate the vehicle drivability and comfortability with different control parameters. A model predictive control (MPC) scheme with softened constraints for this HEV is developed. The new MPC with softened constraints shows its superiority over the MPC with hard constraints as it provides a faster setpoint tracking and smoother clutch engagement. The conversion of some hard constraints into softened constraints can improve the MPC stability and robustness. The MPC with softened constraints can maintain the system stability, while the MPC with hard constraints becomes unstable if some input constraints lead to the violation of output constraints.
Highlights
Controllers for hybrid electric vehicle (HEV) powertrains and speeds can be included model-free or modelbased
A model predictive control (MPC) with horizon state and open loop control prediction subject to dynamic constraints are mainly used to control as real-time the HEV speeds and torques
A recent modelling and control of the dual clutch transmission for HEVs are presented in [2], in which a new controller was designed for synchronizing the dual clutch transmission (DCT) with higher performances and lower fuel consumption
Summary
Controllers for HEVs powertrains and speeds can be included model-free or modelbased. A recent modelling and control of the dual clutch transmission for HEVs are presented in [2], in which a new controller was designed for synchronizing the dual clutch transmission (DCT) with higher performances and lower fuel consumption. Another MPC for an autonomous driving vehicle is developed in [3], in which the MPC was used to drive the HEV to exactly track the given feasible trajectories. The authors of [14] reviewed the latest model-based controllers in the market to assess the improvement of energy management for HEVs, and, in this study, the MPC was used to calculate optimal energy, torque, and speed. The layout of this paper is as following: Section 2 presents the modelling of the parallel HEV; Section 3 introduces the design of the MPC; Section 4 develops the MPC algorithms with softened constraints; Section 5 illustrates the simulations of the MPC for the HEV; and Section 6 is the conclusion
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