Automotive product design is very complex and involves arriving at precise decisions and feasible solutions (with respect to subsystem design specifications, vehicle architecture, change content, materials, geometry, etc.) meeting various functional image and regulatory requirements. It is vital to use various subjective and objective optimization methods while finalizing the specifications of various vehicle subsystems (transmission, engine, body systems, etc.). The present work involves development of a multi-objective multi-disciplinary design optimization (MMDO) approach to optimize the gear pair of an automotive system (SUV/Pick-up platform) with an objective of minimizing the cost and maximizing the performance and transmission bandwidth. Using advanced simulation tools and a DoE-based approach, functional forms were derived for the constraints. The functional forms are the predictive models obtained from various regression, response surface, and machine learning-based methods. The objective functions capture the cost and commonality aspects of the available gearbox design. The concept of cosine similarity is used to arrive at the expressions for objective function that define the commonality aspect of the transmission bandwidth. Tradespace exploration is carried out using advanced optimization algorithms and visualization tools to arrive at optimal solution.
A Methodology for Multi-objective Design Optimization (MDO) of Automotive Transmission Systems
Lect.Notes Mechanical Engineering
National Conference on Multidisciplinary Analysis and Optimization ; 2021 October 07, 2021 - October 09, 2021
2022-09-25
11 pages
Article/Chapter (Book)
Electronic Resource
English
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