智能网联汽车节能优化关键问题与研究进展

汽车保有量的增加和能耗排放法规日益严格的限制给车辆节能减排提出了巨大挑战，网联化、智能化和电气化是提高未来交通效率和减少公路能源消耗的三大支柱。为了全面了解智能网联汽车节能减排的前沿问题与研究进展，对当前经济驾驶领域的重点问题进行了总体概述。首先，从广义的能量转换角度总结了智能车辆节能优化技术的本质和3个过程，其中Wheels to Distance环节的车辆系统优化是挖掘汽车节能潜力的重要一环，针对其介绍了智能网联汽车节能优化问题的基本数学原理；其次，从智能运输系统的各类非同源异构数据出发，分别从人-车交互、车-车通信、车-路感知三方面阐述来源于"人-车-路"交互体系的智能信息与数据；然后，针对单车智能网联环境下的多维度信息与先进控制技术相结合的关键问题，从考虑道路坡度预测巡航控制、跟车工况预测巡航控制、智能辅助驾驶和车道变换等应用场景进行具体介绍；针对"人-车-路-云"多源异构环境下车辆行为协同节能关键科学问题，从经济驾驶、多车协同节能、道路交叉口车路协同节能和车云协同节能等方面详细介绍研究现状；并进一步介绍电气化公路系统的前瞻性研究，说明融合智能化信息的E-highway节能潜力和智能重型商用车协同节能的未来发展趋势。最后，总结并梳理智能化信息对于提升车辆节能的重要影响，并展望了其在理论与实际层面遇到的挑战。

Key Problems and Research Progress of Energy Saving Optimization for Intelligent Connected Vehicles

The continual increase in vehicle parc and stricter restrictions on energy consumption regulations have posed substantial challenges for vehicle energy conservation and emission reduction. Three pillars, namely networking, intelligence, and electrification, could improve the efficiency of transportation, energy conservation, and emission reduction in the future. Considering the frontier problems and research progress of energy saving and emission reduction in the context of intelligent connected vehicles, a general overview of current key issues in the field of eco-driving is presented. First, from the perspective of energy conversion in a broad sense, this paper summarizes the essence and three processes of energy-saving approaches in intelligent vehicles, wherein wheels to distance optimization in the vehicle systems is the most important. The basic mathematical principles of energy-saving optimization in terms of wheel-to-distance are introduced. Second, considering diverse non-homologous and heterogeneous data of intelligent transportation systems, various sources of intelligent information are described from three aspects:human-vehicle interaction, vehicle-to-vehicle communication, and vehicle-road perception. Third, for a single vehicle in an intelligent networked environment, aiming at the key issue of the combination of multi-dimensional information and advanced control technologies, specific applications are discussed from four aspects:predictive cruise control considering road slope, predictive cruise control for car-following conditions, engine start/stop and neutral taxiing, and lane change. For the human-vehicle-road-cloud under a multi-source heterogeneous environment, aiming at the key scientific issue of collaborative energy-savings based on vehicle behaviors, the research status is clarified from four aspects:eco-driving, collaborative energy saving of multiple vehicles, collaborative energy saving at road intersections, and collaborative energy saving based on vehicle-cloud. Furthermore, pioneering research on electric highway systems is described in detail to elaborate on the future trend of collaborative energy saving in the context of intelligent heavy commercial vehicles. Finally, the importance of intelligent information for improving the energy-saving performance of intelligent connected vehicles is summarized, and the challenges that may be encountered at the theoretical and practical levels are discussed.