Technical Paper
Energy Management Strategy for Plug-in Hybrid Vehicles Based on Model Predictive Control and Local Encryption Dynamic Programming
2024-04-09
2024-01-2781
A model predictive control (MPC) energy management strategy (EMS) coupled with offline dynamic programming (ODP) based on historical average vehicle speed, ODP-MPC, is proposed in this paper. The effectiveness of ODP-MPC is verified using historical traffic flow datasets from the open literature. The simulation results show that ODP-MPC can reduce fuel consumption by 1.1% to 7.3% compared to MPC. Moreover, at the prediction area Hp=3(3s), the fuel consumption of ODP-MPC is only 2.1% higher than that of the DP algorithm. This indicates that ODP-MPC can approximate the theoretical fuel economy. As for the computational effort, the online computation time of ODP-MPC is improved by 6.3%~22.9% compared to MPC, but still less than the 1s time step. Reducing the number of grid cells (m) or increasing the distance step (distf) in offline DP reduces the offline computational cost and the fuel economy of ODP-MPC.
