Open AccessFast velocity trajectory planning and control algorithm of intelligent 4WD electric vehicle for energy saving using time‐based MPC
Author(s) -
Wu Dongmei,
Li Yue,
Du Changqing,
Ding Haitao,
Li Yang,
Yang Xiaobo,
Lu Xinyue
Publication year - 2019
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2018.5103
Subject(s) - model predictive control , horizon , control theory (sociology) , trajectory , time horizon , energy (signal processing) , energy consumption , discrete time and continuous time , electric energy consumption , electric vehicle , control (management) , computer science , vehicle dynamics , engineering , mathematical optimization , automotive engineering , mathematics , electric energy , artificial intelligence , power (physics) , statistics , physics , geometry , quantum mechanics , astronomy , electrical engineering
For intelligent four‐wheel‐drive (4WD) electric vehicle (EV), the vehicle speed can be planned and controlled for energy saving based on the slope information of road ahead. To reduce the calculation load of the optimisation algorithm, the model predictive control (MPC) method is formulated based on the time horizon in this study. Furthermore, a fast gradient method based control tool‐GARMPC is used to solve the optimisation problem. First, the longitudinal dynamics model of 4WD EV based on time horizon and distance horizon is established based on the road slope information, respectively. Second, the MPC problem based on the time‐discrete model is formulated and solved by GARMPC tool. For comparison, a dynamic program (DP) control method is introduced based on the distance‐discrete model. Finally, the simulation is conducted under a designed road condition and a real measured road condition. The results show that the time‐horizon based MPC method can significantly reduce the energy consumption compared with the proportion integration differentiation control method, which is similar to the driver's operation. Compared with the DP optimisation method, the time‐based MPC method reduces the calculation time to smaller than 1 ms, which is essential for real‐time application in a road vehicle.