论文标题
电动汽车的脉冲和机驱动自适应巡航控制系统
A Pulse-and-Glide-driven Adaptive Cruise Control System for Electric Vehicle
论文作者
论文摘要
随着车辆上的自适应巡航控制系统（ACC）如今已发达，车辆制造商越来越多地利用了新一代智能车辆的技术。脉搏和机（PNG）策略是一种有效的驾驶策略，可减少传统的油耗车辆的燃油消耗。但是，目前的研究很少关注PNG对电动汽车（EV）的节能效应的验证，并将PNG嵌入ACC中。本文提出了一种由脉冲和流动驱动的自适应巡航控制系统（PGACC）模型，该模型将PNG策略作为具有巡航控制（CC）的平行功能（CC），并验证PNG是通过使用智能遗传型粒子旋转型和粒子旋转的PNG操作来优化PNG运行的EV上的有效节能策略，以实现EV的有效省动策略。本文基于PGACC的性能和再生制动的性能，构建了EV的模拟模型。对PNG能量性能进行了优化，并评估再生制动对PNG能量性能的影响。通过PNG优化，与传统ACC中的CC操作相比，PGACC中的PNG操作可以减少EV的28.3％的能源成本，这证明PNG是EV和PGACC的有效节能策略，是EV的有前途的选择。
As the adaptive cruise control system (ACCS) on vehicles is well-developed today, vehicle manufacturers have increasingly employed this technology in new-generation intelligent vehicles. Pulse-and-glide (PnG) strategy is an efficacious driving strategy to diminish fuel consumption in traditional oil-fueled vehicles. However, current studies rarely focus on the verification of the energy-saving effect of PnG on an electric vehicle (EV) and embedding PnG in ACCS. This paper proposes a pulse-and-glide-driven adaptive cruise control system (PGACCS) model which leverages PnG strategy as a parallel function with cruise control (CC) and verifies that PnG is an efficacious energy-saving strategy on EV by optimizing the energy cost of the PnG operation using Intelligent Genetic Algorithm and Particle Swarm Optimization (IGPSO). This paper builds up a simulation model of an EV with regenerative braking and ACCS based on which the performance of PGACCS and regenerative braking is evaluated; the PnG energy performance is optimized and the effect of regenerative braking on PnG energy performance is evaluated. As a result of PnG optimization, the PnG operation in the PGACCS could cut down 28.3% energy cost of the EV compared to the CC operation in the traditional ACCS which verifies that PnG is an effective energy-saving strategy for EV and PGACCS is a promising option for EV.
