Synthesis tool for conventional and hybrid powertrains

用于传统和混合动力系统的综合工具

• 批准号: 433517773
• 负责人: Professor Dr.-Ing. Peter Eilts
• 金额: --
• 依托单位: Institut für Fahrzeugtechnik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2020
• 资助国家: 德国
• 起止时间: 2019-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/433517773?language=en
• 关键词: Synthesis; tool; conventional; hybrid; powertrains

In this research project, a synthesis tool for conventional and hybrid powertrain concepts will be developed. A computer-assisted synthesis enables to investigate all theoretically conceivable combinations of the aggregate-specific design parameters. Therefore, promising concepts can be identified depending on the defined requirements and evaluation criteria. By generating all theoretically conceivable parameter combinations, new variants of topologies, aggregates or components can be identified by means of synthesis. The synthesis programs available at the institutes of the two applicants will be further developed and coupled in the framework of this project in order to build a tool for powertrain synthesis. Since the number of degrees of freedom of a powertrain is very high, new approaches are needed to be able to realize an optimization in the sense of the defined criteria. For this reason, an identifier is developed which enables optimization of the overall system based on physical expertise. For this purpose, potential parameters are developed which the identifier uses to choose suitable measures in order to optimize the properties of the powertrain based on the defined evaluation criteria. The decisions that the identifier makes during a synthesis process are supported by a data-based, self-learning system. As a result, existing expert knowledge in the form of physical connections as well as development experience is transferred into algorithms as well as program structures and used for the optimization of complex systems. The two applicants cover the internal combustion engine and transmission. As a consequence, the consideration of electric machines, power electronics and batteries is simplified in this project. However, if the project has been successfully completed, a further research project with additional partners will be pursued in order to be able to consider the electrical aggregates of a powertrain more accurately.

在这个研究项目中，将开发一个用于传统和混合动力系统概念的综合工具。计算机辅助合成能够研究聚集体特定设计参数的所有理论上可能的组合。因此，可以根据定义的要求和评估标准确定有前途的概念。通过生成所有理论上可能的参数组合，可以通过合成识别拓扑、聚集体或组件的新变体。两个申请人的研究所提供的综合程序将在本项目的框架内进一步开发和耦合，以构建动力系统综合工具。由于动力系统的自由度非常高，因此需要新的方法来实现在所定义的标准的意义上的优化。出于这个原因，开发了一种识别器，该识别器能够基于物理专业知识优化整个系统。为此，开发潜在参数，识别器使用这些潜在参数来选择合适的措施，以便基于所定义的评估标准来优化动力系的特性。识别器在合成过程中做出的决定由基于数据的自学习系统支持。因此，以物理连接形式存在的专家知识以及开发经验被转化为算法和程序结构，并用于复杂系统的优化。这两个申请人涵盖内燃机和变速器。因此，在该项目中，电机、电力电子和电池的考虑被简化。然而，如果该项目已经成功完成，将与其他合作伙伴进行进一步的研究项目，以便能够更准确地考虑动力系统的电气集合。