The energy utilization efficiency of autonomous electric vehicles is seriously affected by the longitudinal motion control performance. However, the longitudinal motion control is constrained by the driving scene. This article proposes an energy-saving optimization and control (ESOC) method to improve the energy utilization efficiency of autonomous electric vehicles. In ESOC, the constraints from the driving scene are thoroughly considered, and the autonomous driving scene constraints are mapped to the vehicle dynamics and control domain. On this basis, the efficiency self-searching method and the multiconstraint energy-saving control strategy are designed. The main ideology of the proposed ESOC is that the energy utilization efficiency of an autonomous electric vehicle can be improved by optimizing and controlling the operation point distribution of the powertrain efficiency. The experimental results demonstrate that the operation point distribution of the autonomous electric vehicle's powertrain efficiency can be well optimized by the proposed ESOC, and the energy consumption results indicate that the proposed ESOC outperforms the state-of-the-art methods.

中文翻译：

---

考虑多约束的自动驾驶汽车节能优化与控制。

纵向运动控制性能严重影响了自动驾驶电动汽车的能源利用效率。然而，纵向运动控制受到驾驶场景的约束。本文提出了一种节能优化控制方法，以提高自动驾驶汽车的能源利用效率。在ESOC中，将充分考虑来自驾驶场景的约束，并将自主驾驶场景的约束映射到车辆动力学和控制域。在此基础上，设计了效率自搜索方法和多约束节能控制策略。提出的ESOC的主要思想是，通过优化和控制动力总成效率的工作点分布，可以提高自动驾驶电动汽车的能源利用效率。实验结果表明，提出的ESOC可以很好地优化自动驾驶电动汽车动力总成效率的工作点分布，而能耗结果表明，提出的ESOC优于最新方法。