论文标题
综合的近似动态编程和等效的消费策略，以在连接和自动化的车辆中进行生态驾驶
Integrated Approximate Dynamic Programming and Equivalent Consumption Minimization Strategy for Eco-Driving in a Connected and Automated Vehicle
论文作者
论文摘要
本文着重于与混合电动动力总成的连接和自动化车辆（CAVS）的速度计划和能源管理问题。生态驾驶问题在空间域中被提出为非线性动态优化问题，其中有关即将到来的速度限制和道路地形的信息被认为是先验的。为了解决这个问题，提出了一种基于新颖的动态编程（DP）优化方法，其中嵌入了因果等效的消耗策略（ECMS）。使用实验数据验证了预测现实世界路线上能源消耗的基础车辆模型。 此外，提出了多层层次控制体系结构，作为在车辆中实时实现的途径。引入了DP-ECMS算法，以解决长匹马优化问题，然后使用近似动态编程（ADP）中的原理进行改编，以进行逐渐的视野实现。然后对传统DP解决方案的计算经济替代方案进行基准测试和评估。
This paper focuses on the velocity planning and energy management problems for Connected and Automated Vehicles (CAVs) with hybrid electric powertrains. The eco-driving problem is formulated in the spatial domain as a nonlinear dynamic optimization problem, in which information about the upcoming speed limits and road topography is assumed to be known a priori. To solve this problem, a novel Dynamic Programming (DP) based optimization method is proposed, in which a causal Equivalent Consumption Minimization Strategy (ECMS) is embedded. The underlying vehicle model to predict energy consumption over real-world routes is validated using experimental data. Further, a multi-layer hierarchical control architecture is proposed as a pathway to real-time implementation in a vehicle. The DP-ECMS algorithm is introduced for a long-horizon optimization problem, and then adapted for a receding horizon implementation using principles in Approximate Dynamic Programming (ADP). This computationally economical alternative to the traditional DP solution is then benchmarked and evaluated.
