Automated Park and Charge: Concept and Energy Demand Calculation

Axel Sturm, M. Kascha, M. A. Mejri, Roman Henze, L. Heister, A. Mueck
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Abstract

In this paper, we present the concept of automated park and charge functions in two different use cases. The main use case is automated driving in production and the other use case is within automated valet parking in parking garages. The automated park and charge in production is developed in the scope of the publicly funded project E-SELF in Germany. The central aim of this project is the development and integration of automated driving at the end-of-line in the production at Ford Motor Company's manufacturing plant in Cologne. The driving function thereby is mostly based upon automated valet driving with an infrastructure-based perception and motion planning. Especially for electric vehicles, the state of charge of the battery is critical, since energy is needed for all testing and driving operations at the end-of-line. In addition, long shipping, combined with a specific state of charge requirement at customer delivery, require recharging at the production facility. This recharging process is also an automated process with a robot and demands direct connection to the driving function. The main scope of this paper is the introduction of an energy demand calculation for the necessary charging operations. The developed tool allows multiple analyses for identifying further potentials in the production line. Based on a study of a Ford Mach-E it showed, that the highest energy demands are due to battery self-discharging during standstill, especially in the summer months. For a transport to the customer by train and truck, an energy demand of 2kWh within the production facility is estimated. Longer transport times, e.g. when the vehicle is shipped to the customer, the energy demand increases up to 4 kWh. Depending on the vehicle and application, the developed toolchain allows future optimization of recharging processes and also promotes automated park and charging, where the demands can be individually calculated by the park management system.
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自动泊车和充电:概念和能源需求计算
在本文中,我们介绍了两个不同使用案例中的自动泊车和收费功能概念。主要用例是生产中的自动驾驶,另一个用例是停车场中的自动代客泊车。生产中的自动泊车和充电功能是在德国公共资助项目 E-SELF 的范围内开发的。该项目的核心目标是在位于科隆的福特汽车公司制造厂开发并整合生产终端的自动驾驶功能。因此,驾驶功能主要基于自动代客驾驶,以及基于基础设施的感知和运动规划。特别是对于电动汽车来说,电池的充电状态至关重要,因为在生产线末端的所有测试和驾驶操作都需要能量。此外,由于运输时间较长,加上客户交货时对充电状态的特殊要求,需要在生产设施内进行充电。该充电过程也是一个使用机器人的自动化过程,需要与驱动功能直接连接。本文的主要内容是介绍必要充电操作的能源需求计算。所开发的工具可进行多种分析,以确定生产线的进一步潜力。基于对福特 Mach-E 的研究表明,最高的能源需求是由于静止时的电池自放电,尤其是在夏季。通过火车和卡车向客户运输时,估计生产设施内的能源需求为 2 千瓦时。如果运输时间较长,例如将车辆运送给客户,则能源需求会增加到 4 千瓦时。根据车辆和应用的不同,所开发的工具链可优化未来的充电流程,并促进自动停车和充电,其中停车管理系统可单独计算需求。
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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