Synthesis tool for conventional and hybrid powertrains

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。计算机辅助合成可以研究所有理论上可想象的特定设计参数的组合。因此，可以根据已定义的需求和评估标准来确定有希望的概念。通过生成所有理论上可想象的参数组合，可以通过合成的方式识别拓扑、聚集体或组件的新变体。两个申请人的研究所现有的合成程序将在本项目的框架内进一步开发和结合，以建立动力总成合成工具。由于动力系统的自由度非常高，因此需要新的方法来实现已定义标准意义上的优化。因此，开发了一种标识符，它可以基于物理专业知识对整个系统进行优化。为此，开发了潜在参数，识别器使用这些参数来选择合适的措施，以便根据定义的评估标准优化动力总成的性能。标识符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，现有的物理连接形式的专家知识和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。这两家申请公司负责内燃机和变速器。因此，本项目简化了对电机、电力电子和电池的考虑。然而，如果该项目已经成功完成，为了能够更准确地考虑动力总成的电气聚合，将与其他合作伙伴进行进一步的研究项目。

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.