High nonlinearity of BEV's stepped automatic transmission design objectives and its optimal solution by a novel ISA-RSA
The battery electric vehicle's (BEV's) stepped automatic transmission (SAT) has a significant influence on the power and economic performance of the new-energy vehicle system dynamics. The SAT entails a complex design process, where the transmission ratio parameter and the control strategy...
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| Veröffentlicht in: | Energy (Oxford) Jg. 282; S. 128834 |
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| 1. Verfasser: | |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
01.11.2023
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| Schlagworte: | |
| ISSN: | 0360-5442 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | The battery electric vehicle's (BEV's) stepped automatic transmission (SAT) has a significant influence on the power and economic performance of the new-energy vehicle system dynamics. The SAT entails a complex design process, where the transmission ratio parameter and the control strategy are interactively coupled, causing a difficulty in achieving a globally optimal solution. The actual design process involves multiple design objectives and incurs high design costs. The purpose of this study is to explore the variation characteristics of the design objectives of BEV's SAT and propose a transmission parameter optimization design method with reduced design costs. The paper investigates the interactive coupling property of the transmission ratio parameter and the control strategy, analyzing the high nonlinearity of SAT design objectives using the example of two-gear transmission. It proposes a design method that combines a heuristic optimization algorithm and an estimation model (Method Ⅲ), and a design method that utilizes an improved simulated annealing algorithm and a region search algorithm (ISA-RSA, Method Ⅳ). These methods are compared with a design method based on combination tests using the traversing method (Method Ⅰ) and a design method based on the heuristic optimization algorithm (Method Ⅱ). The results indicate that Method I incurs high design costs with limited effectiveness, while Method II exhibits unstable economic performance and integrated design objectives with fluctuations. Method III is highly dependent on the accuracy of the estimated model and performs poorly in optimizing acceleration time. However, Method Ⅳ, with low design costs, demonstrates remarkable optimization ability to solve high nonlinearity problems and exhibits a high probability of converging to the area near the globally optimal solution. This paper also aims to provide a direct solution to high design cost and highly nonlinear design objective problems in other engineering fields. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0360-5442 |
| DOI: | 10.1016/j.energy.2023.128834 |