Enhanced Derivation of Customer-Specific Drive System Design Parameters with Time Frame-Based Maximum Load Analysis
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, pr...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
|
| Series: | Vehicles |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-8921/5/1/17 |
| _version_ | 1797608710174932992 |
|---|---|
| author | Raphael Mieth Fabian Markschies Ruixin Zhou Frank Gauterin Arnd Stephan |
| author_facet | Raphael Mieth Fabian Markschies Ruixin Zhou Frank Gauterin Arnd Stephan |
| author_sort | Raphael Mieth |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T05:47:22Z |
| format | Article |
| id | doaj.art-9f0c46cd87fd4a219bdfb115e38db143 |
| institution | Directory Open Access Journal |
| issn | 2624-8921 |
| language | English |
| last_indexed | 2024-03-11T05:47:22Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Vehicles |
| spelling | doaj.art-9f0c46cd87fd4a219bdfb115e38db1432023-11-17T14:20:11ZengMDPI AGVehicles2624-89212023-02-015130632010.3390/vehicles5010017Enhanced Derivation of Customer-Specific Drive System Design Parameters with Time Frame-Based Maximum Load AnalysisRaphael Mieth0Fabian Markschies1Ruixin Zhou2Frank Gauterin3Arnd Stephan4Institute of Vehicle System Technology, Karlsruhe Institute of Technology, 76131 Karlsruhe, GermanyMercedes-Benz AG, 70327 Stuttgart, GermanyMercedes-Benz AG, 70327 Stuttgart, GermanyInstitute of Vehicle System Technology, Karlsruhe Institute of Technology, 76131 Karlsruhe, GermanyInstitute of Railway Vehicles and Railway Technology, TU Dresden, 01069 Dresden, GermanyOnly 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.https://www.mdpi.com/2624-8921/5/1/17design of vehicle drive systemsanalysis of customer datasequence of time series |
| spellingShingle | Raphael Mieth Fabian Markschies Ruixin Zhou Frank Gauterin Arnd Stephan Enhanced Derivation of Customer-Specific Drive System Design Parameters with Time Frame-Based Maximum Load Analysis Vehicles design of vehicle drive systems analysis of customer data sequence of time series |
| title | Enhanced Derivation of Customer-Specific Drive System Design Parameters with Time Frame-Based Maximum Load Analysis |
| title_full | Enhanced Derivation of Customer-Specific Drive System Design Parameters with Time Frame-Based Maximum Load Analysis |
| title_fullStr | Enhanced Derivation of Customer-Specific Drive System Design Parameters with Time Frame-Based Maximum Load Analysis |
| title_full_unstemmed | Enhanced Derivation of Customer-Specific Drive System Design Parameters with Time Frame-Based Maximum Load Analysis |
| title_short | Enhanced Derivation of Customer-Specific Drive System Design Parameters with Time Frame-Based Maximum Load Analysis |
| title_sort | enhanced derivation of customer specific drive system design parameters with time frame based maximum load analysis |
| topic | design of vehicle drive systems analysis of customer data sequence of time series |
| url | https://www.mdpi.com/2624-8921/5/1/17 |
| work_keys_str_mv | AT raphaelmieth enhancedderivationofcustomerspecificdrivesystemdesignparameterswithtimeframebasedmaximumloadanalysis AT fabianmarkschies enhancedderivationofcustomerspecificdrivesystemdesignparameterswithtimeframebasedmaximumloadanalysis AT ruixinzhou enhancedderivationofcustomerspecificdrivesystemdesignparameterswithtimeframebasedmaximumloadanalysis AT frankgauterin enhancedderivationofcustomerspecificdrivesystemdesignparameterswithtimeframebasedmaximumloadanalysis AT arndstephan enhancedderivationofcustomerspecificdrivesystemdesignparameterswithtimeframebasedmaximumloadanalysis |