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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM16429
Volume:
6 |
9 |
Sep 2022
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
To develop and validate the testing of electric axle systems, a strong testing methodology optimally balances CAE and actual testing. CAE provides a cost- and time-efficient tool for evaluating design parameters in the hands of a manufacturer who is optimizing structures, predicting which likely failure model to use, and improving the overall performance of the system. CAE simulations use sophisticated computational models such as finite element analysis (FEA) and multi-body dynamics (MBD) to assess not only the structural integrity but also the thermal management and efficiency of a system without the need for any physical prototypes. Nevertheless, due to the fact that real-world accuracy and reliability cannot be guaranteed without physical testing, progression in CAE does not imply the end of physical validation. Material inconsistency, variation of an environment from that assumed, and unforeseen mechanical interactions are extremely potent differentiating factors. Physical testing applies engineering commentary on CAE predictions, pinpoints unforeseen issues, and feeds back into design to enhance durability and safety. However, physical testing could prove to be expensive and time- consuming, outlaying consumable materials for testing; besides, it is also energetically expensive. In the present article, we will consider the compromise between the two methodologies and weigh their advantages and disadvantages. While CAE offers methods to save cost and reduce waste, physical tests guarantee the verification of realistic operating conditions. A complementary method integrating the combination of CAE and physical testing will maximize the electric axle validation by exploiting the CAE capabilities for predictive purposes, while being confirmed with real-world feasibility through concentrated experimental corroboration. This hybrid approach results in better efficiency, shorter time for development cycles, and goes a long way to promoting sustainability in the automotive industry. Implementation of a mildly balanced framework for validation assures manufacturers of high-performing, durable, and environmentally friendly electric axle systems.
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Publication Date
9/26/2022
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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