Speed Trajectory Optimization Method for Electric Vehicles Based on Driving Style

In real driving conditions, speed trajectory optimization is an important part of the energy-saving driving assistance system of smart cars, and it can contribute to increase the cruising range. However, the existing speed trajectory optimization research for vehicles mainly focuses on energy consumption and does not consider whether the optimized trajectory can meet the driver’s driving style requirements. In response to this problem, this article establishes an electric vehicle energy consumption model and discusses the difference between the trajectory reflecting driving style (TRDS) and the optimal trajectory of energy consumption (OTOEC). Based on the driving speed trajectory and acceleration trajectory of the driver, this article obtains trajectory clusters reflecting the driving style of the driver by trajectory data mining and establishes the driving style characteristic space (DSCS) based on these clusters and proposes a speed trajectory optimization method based on driving style finally. Compared with the TRDS, the energy consumption of the trajectory obtained by this method can reduce significantly. The trajectory obtained by the method can reflect the driving style of the driver to a large extent compared with the OTOEC. The simulation results verify the effectiveness of the method.