Experimental Analysis of Powertrain Test Bed Dynamometers for Black Box-Based Digital Twin Generation

Henrik Schmidt, G. Prokop
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Abstract

The recent developments in the automotive industry denote a significant increase in embedded control units, algorithms and connectivity inside the vehicle and with its environment. All trends require a substantial increase in the virtualization of present development activities. Here, the deployed methods must be proven valid and optimized strategies for building and identifying real-time simulation models have to be developed. The context of the present work is the validation of low-frequency powertrain oscillations based on drivability-relevant properties at a full-vehicle level. An early powertrain validation at the subsystem level demands real-time modelling of the specimen, the test bed and the residual vehicle. The simulation models must be proven valid in the drivability-relevant frequency range of up to 30 Hz. Therefore, the reference test bed setup is presented together with the selected design of experiments. Then, a system identification process in the time and frequency domain is conducted to allow fast and reliable identification of the first torsional natural mode of the powertrain and the time characteristic of the dynos stated in dead time and group delay. In conclusion, the authors present a method for efficient drivability-related dynamometer characterization for blackbox-based modeling up to 1 kHz.
基于黑箱的数字孪生发电动力系统试验台测功机实验分析
汽车行业的最新发展表明,嵌入式控制单元、算法和车辆内部及其与环境的连接显著增加。所有趋势都需要大量增加目前发展活动的虚拟化。在这里,部署的方法必须被证明是有效的,并且必须开发用于构建和识别实时仿真模型的优化策略。目前的工作背景是在整车水平上基于驾驶相关特性验证低频动力总成振荡。在子系统层面的早期动力系统验证需要对样品、试验台和剩余车辆进行实时建模。仿真模型必须在高达30hz的驾驶相关频率范围内被证明是有效的。因此,本文给出了参考试验台的设置和实验设计的选择。然后,对系统进行时域和频域识别,以快速、可靠地识别动力系统的一阶扭转固有模态以及以死区时间和群延迟表示的动力系统的时间特性。总之,作者提出了一种有效的驾驶性能相关的测功机表征方法,用于基于黑盒的建模,最高可达1khz。
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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