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Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

机译：基于行驶周期信息统计处理的混合动力汽车替代储能系统设计

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摘要

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology.udThis work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed.udResults show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.
机译：混合动力汽车代表了汽车制造商的未来，因为它们可以改善燃油经济性并减少污染物排放。混合动力总成的关键组成部分是能量存储系统，它确定了车辆存储和再利用能量的能力。尽管基于电池和超级电容器的电气化储能系统（ESS）是一种行之有效的技术，但是基于机械，液压和气动设备的替代储能系统（AESS）却引起了人们的兴趣，因为它们提供了实现低成本的可能性轻度混合动力车辆。当前，大多数设计方法论文献都集中在不适合AESS设计的电子ESS上。在这场比赛中，俄亥俄州立大学开发了一种替代能源存储系统的设计方法。 ud这项工作着重于开发驾驶循环分析方法，该方法是替代能源存储系统设计程序的关键组成部分。所提出的方法基于统计方法来分析代表车辆典型用途的驾驶时间表。驾驶数据被分解为动力事件序列，即牵引和制动事件，并针对它们中的每一个，计算与能量有关的指标和动态指标。通过聚类过程和统计综合方法，可以确定统计上相关的指标。这些度量定义了代表循环的制动事件。通过将这些事件用作替代能源存储系统设计方法的输入，可以获得不同的系统设计。它们每个都具有属性，即系统体积和重量。在工作的最后一部分中，通过引入和计算与能量转换效率相关的度量，对设计进行仿真评估。最后，比较设计以考虑属性和效率值。为了使驾驶数据提取和合成过程自动化，已经开发了一个基于Matlab的特定脚本。 ud结果表明，基于统计方法的驾驶周期分析方法可以提取和合成周期代表数据。基于周期统计相关指标的设计尺寸适当，相对于期望值具有令人满意的效率值。一种例外是基于循环最坏情况的设计，它对应于常规电子ESS设计方法所采用的相同方法。在这种情况下，将产生效率低下的重型系统。拟议的新方法似乎是替代能源存储系统设计的有效和一致的支持。

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    Bolletta Alberto;

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  • 年度 2011
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  • 正文语种 {"code":"en","name":"English","id":9}
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