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 optim...
详细信息
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) controlmethod 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 controlmethod, 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 1ms, which is essential for real-time application in a road vehicle.
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