Autonomous driving related technologies have become a hot topic in academia and industry. Planning control is one of the core technologies of autonomous driving, which is conducive to vehicles safe and efficient driving. This paper proposes a novel optimal speed control algorithm, which considers the power system's energy consumption, the speed limit on the road, and the safe distance of the vehicle in front. An optimal speed control model of “From battery to wheel” energy consumption is established by constructing a performance index function based on the best-fitting formula of motor power, motor speed and torque. Based on the optimal control principle, the fourth-order ordinary differential equation of the speed control model is established, based on the indirect adjoining approach, the speed control model under the restriction of the road speed limit and safe distance of the preceding vehicle is derived and the analytical expression is obtained. Under the restriction of the road speed limit and safe distance of the preceding vehicle, the model predictive control method is introduced, the urban working conditions in the NEDC cycle are selected for simulation, and the optimal control input is solved in real-time, compared with the intelligent driver driving strategy, this algorithm is proved to be superior in the aspect of vehicle speed optimization control. Finally, the influence mechanism of the road speed limit constraint on the vehicle speed control is analyzed. This paper realizes the design of the optimal speed control algorithm for energy consumption under various constraints. The results can be used to guide the energy-saving driving of vehicles, and provide theoretical guidance for ecological driving technology in the context of intelligent transportation.
A Novel Speed Control Strategy for Electric Vehicles with Optimal Energy Consumption under Multiple Constraints
Sae Technical Papers
WCX SAE World Congress Experience ; 2023
2023-04-11
Conference paper
English
Optimal Energy Consumption Algorithm Based on Speed Reference Generation for Urban Electric Vehicles
British Library Conference Proceedings | 2015
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