Enhanced Derivation of Customer-Specific Drive System Design Parameters with Time Frame-Based Maximum Load Analysis

Raphael Mieth, Fabian Markschies, Ruixin Zhou, F. Gauterin, A. Stephan
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Abstract

Only a small part of the high performance of electric drive systems in vehicles is used in everyday operation by customers. As a result, most drives are not operated in the optimum efficiency range. Designing a suitable drive system, whose performance is aligned with actual customer requirements, presents the potential to increase efficiency. Based on the findings of previous research, this paper serves to complement an existing method, which already introduced the basic method of transferring statistical customer data into relevant parameters for the design of a customer-specific drive system. In order to improve the method, further criteria for the selection of relevant time series come into place. Furthermore, the impact on maximum loads resulting from various sequences of the selected time series is identified and evaluated with time frame-based analysis. A new approach for the effective computation of maximum design-relevant loads in the admissible time frame range is introduced and validated. By taking this approach, the sensitivity of the derived design parameters regarding various time series sequence is evaluated in the context of selected datasets. In addition, concatenations of time series are identified which may have a relevant influence on the maximum loads. Consequently, the design process is safeguarded thoroughly against potential maximum loads as well as the associated thermal stresses.
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基于时间框架的最大负载分析增强了客户特定驱动系统设计参数的推导
在车辆的高性能电力驱动系统中,只有一小部分被客户用于日常操作。因此,大多数驱动器不能在最佳效率范围内运行。设计一个合适的驱动系统,其性能与客户的实际需求相一致,有可能提高效率。在前人研究成果的基础上,本文对现有方法进行了补充,该方法已经介绍了将客户统计数据转化为客户特定驱动系统设计的相关参数的基本方法。为了改进该方法,进一步制定了选择相关时间序列的标准。此外,通过基于时间框架的分析,确定和评估了所选时间序列的各种序列对最大负载的影响。提出并验证了在允许时间范围内有效计算最大设计相关荷载的新方法。通过采用这种方法,在选定的数据集的背景下评估了推导出的设计参数对各种时间序列序列的敏感性。此外,确定了可能对最大荷载产生相关影响的时间序列的串联。因此,设计过程完全防止潜在的最大负载以及相关的热应力。
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