自动驾驶电动汽车生态驾驶中固定与动态再生制动低速边界的比较

M. Mohammadi, P. Fajri, Farshad Harirchi, R. Sabzehgar
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引用次数: 0

摘要

再生制动(RB)是电动汽车(ev)的功能之一,它不仅有可能提高电动汽车的效率,而且有可能延长这些车辆一次充电的范围。考虑到自动驾驶电动汽车(aev)的速度规划阶段,这种能力有可能提供更多的节能。然而,RB过程受到低速限制,这可能对低速下的能量回收产生不利影响。本文比较了采用固定低速边界和动态低速边界来解决低速RB限制的两种方法,并研究了每种方法对自动驾驶汽车生态驾驶控制问题的影响。采用混合整数线性规划(MILP)方法对生态驾驶问题进行求解,并分析了在预定信号路线下低速运行RB的两个不同案例。结果表明,采用动态LSB可使能量收集提高3.9%。本研究结果进一步说明了在解决自动驾驶汽车生态驾驶问题时考虑动态RB边界的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comparison of Fixed and Dynamic Regenerative Braking Low-Speed Boundary on Eco-driving of Autonomous Electric Vehicles
Regenerative Braking (RB) is one of the capabilities of Electric Vehicles (EVs) which has the potential to not only make EVs more efficient but also extend the range of these vehicles for a single charge. This capability has the potential to provide even more energy savings when considered in the speed planning stage of Autonomous Electric Vehicles (AEVs). The RB process, however, suffers from low-speed limitation which can have adverse effects on energy recuperation at low speeds. This paper presents a comparison of two approaches that use fixed and dynamic low-speed boundaries (LSBs) to address RB limitation at low speeds and studies the impact of each approach on the eco-driving control problem for AEVs. The eco-driving problem is executed with Mixed Integer Linear Programming (MILP), and two different case studies associated with the operation of RB at low speeds are analyzed for a predetermined signalized route. It is shown that up to 3.9% increase in energy harvesting is achievable by employing dynamic LSB. The results of this study further illustrate the importance of considering a dynamic RB boundary when it comes to solving the eco-driving problem for AEVs.
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