基于Radau伪谱法和MPC的智能电动车辆生态驾驶

为优化智能电动车能源消耗，提出了基于Radau伪谱法和模型预测控制算法的智能电动车辆生态驾驶的方案。建立生态驾驶控制模型和能耗模型，结合边界约束和路径约束，构建生态驾驶能耗优化的最优控制问题。通过能耗优化得到最优车速轨迹，将此轨迹作为期望输入，基于模型预测控制( MPC)算法完成生态驾驶控制。实验结果表明：以纯电动车和实际规划路径为例，以最优车速自动行驶的能源消耗少于人工驾驶的能源消耗，验证了文中策略的有效性。

Eco-driving Based on Radau Pseudo-spectral Method and Model Predictive Control for Intelligent Electric Vehicle

Intelligent electric vehicle longitudinal motion energy optimization can save energy and improve vehicle performance. In order to accurately obtain the energy consumption of the vehicle, the energy consumption optimization problem of the longitudinal motion was solved based on Radau pseudo-spectral method. The longitudinal motion model and energy consumption model was established. Combined with the boundary constraints and path constraints, energy consumption optimization optimal control problem was found. The longitudinal optimum speed trajectory was obtained by solving the problem of minimum energy consumption. This trajectory was used as the desired speed input, the speed tracking control was achieved based on the model predictive control ( MPC) algorithm. The experimental results show that, a pure electric vehicles as an example, the policy in this paper can get continuous power consumption value of vehicles traveling, the longitudinal motion with energy-optimized can reduce energy consumption, and the effectiveness of the strategy is verified.