Eco-driving optimal control for electric vehicles with driver preferences

Q1 Engineering Transportation Engineering Pub Date : 2025-03-01 Epub Date: 2025-01-16 DOI:10.1016/j.treng.2025.100302
Roberto Lot , James Fleming , Boli Chen , Simos Evangelou
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Abstract

An optimal control formulation of an eco-driving system for front-wheel drive electric vehicles is proposed in this paper, demonstrating that including an optimal control model of driver preferences in such systems can successfully blend the objective of energy-efficiency with the subjective goals of human drivers, including desired following distances and time headways, a desired vehicle speed, smooth vehicle acceleration, and a comfortable corner negotiation speed. This builds on previous works that developed driver preference models for optimal control, but did not apply them to a realistic model of an EV powertrain to evaluate potential energy savings in practice. The resulting optimal control problem (OCP) is simplified for implementation by using a polynomial approximation of vehicle losses, and a relaxation of regenerative braking constraints that accurately accounts for required braking bias in a front-wheel drive vehicle. In testing, over a simulated 25km journey involving rural, motorway and urban sections, blending driver preferences with energy efficiency in this framework achieves energy savings of 21% with only a 7% decrease in average speed. For car-following scenarios, 10–15% energy savings are achievable with no decrease in average speed.
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基于驾驶员偏好的电动汽车生态驾驶最优控制
本文提出了一种前轮驱动电动汽车生态驾驶系统的最优控制公式,证明在该系统中加入驾驶员偏好的最优控制模型可以成功地将能效目标与人类驾驶员的主观目标(包括期望的跟随距离和时间领先、期望的车辆速度、平稳的车辆加速和舒适的转弯速度)融合在一起。这是建立在先前的研究基础上的,这些研究开发了驾驶员偏好模型,用于最优控制,但并没有将其应用于现实的电动汽车动力系统模型,以评估实际中潜在的节能效果。通过使用车辆损失的多项式近似,以及精确计算前轮驱动车辆所需制动偏差的再生制动约束的放松,简化了所得到的最优控制问题(OCP)。在测试中,在模拟的25公里旅程中,包括农村、高速公路和城市路段,在这个框架中,将驾驶员的偏好与能源效率相结合,在平均速度只降低7%的情况下,节省了21%的能源。对于跟随汽车的场景,在不降低平均速度的情况下,可以节省10-15%的能源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Transportation Engineering
Transportation Engineering Engineering-Automotive Engineering
CiteScore
8.10
自引率
0.00%
发文量
46
审稿时长
90 days
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