The traffic light in urban areas dominates the traffic flow, resulting in variation of energy consumption of the vehicles involved. To mitigate the impact of traffic bias on the energy efficiency of electric vehicles (EVs), this article proposes an event-driven energy-efficient driving control (EEDC) strategy based on a receding horizon two-stage control framework, which harnesses the Internet of Vehicles to incorporate the traffic light and preceding vehicle for adaption of different driving scenarios. At the core of the first stage are the vehicle driving event classification rules, which classified the urban traffic scenarios into four events. This article contributes to empirical solutions on the design of the traffic scenario classifier considering conflict goals, including driving efficiency and safety. In the second stage, the speed trajectory in each driving event is optimized using Pontryagin’s minimum principle to reduce vehicle energy consumption. A real-time solution for the energy-efficient driving problem is derived with the consideration of vehicle dynamics, control input, and speed limit constraints. Finally, extensive simulations and road tests are conducted to evaluate the effectiveness of the EEDC. The results show that the EEDC is excellent in energy efficiency improvement over two benchmark strategies in different traffic scenarios while satisfying the constraints in inter-vehicle driving safety and travel time. Moreover, the road tests demonstrate that the EEDC is capable of energy saving in real-world driving.

中文翻译：

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城市交通中联网电动汽车事件驱动的节能驾驶控制


城市地区的交通信号灯主导着交通流量，导致车辆的能耗存在差异。为了减轻交通偏差对电动汽车（EV）能源效率的影响，本文提出了一种基于后退两阶段控制框架的事件驱动的节能驾驶控制（EEDC）策略，该策略利用了物联网车辆将红绿灯和前车结合起来，以适应不同的驾驶场景。第一阶段的核心是车辆驾驶事件分类规则，将城市交通场景分为四种事件。本文为考虑冲突目标（包括驾驶效率和安全性）的交通场景分类器设计提供了实证解决方案。第二阶段，利用庞特里亚金极小原理对每次驾驶事件中的速度轨迹进行优化，以降低车辆能耗。考虑车辆动力学、控制输入和速度限制约束，得出节能驾驶问题的实时解决方案。最后，进行广泛的模拟和道路测试来评估 EEDC 的有效性。结果表明，在不同交通场景下，EEDC在满足车辆间驾驶安全和出行时间约束的同时，比两种基准策略的能效提升表现优异。此外，道路测试表明，EEDC能够在实际驾驶中实现节能。