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Title: Investigating an intelligent concept design tool for automotive car body design
Author: Sugiono
ISNI:       0000 0004 2751 6437
Awarding Body: University of Derby
Current Institution: University of Derby
Date of Award: 2012
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The newly designed car in the automotive industry should meet the customers' requirements, e.g. the outlook of the car, size of the car, usage of the car, among other requirements. It must still consider the factors of social life, resources and environmental problems during the automotive design, such as fuel consumption, emission, global warming, noise, accidents etc. [1], [2], [3]. As a result, the right concept of automotive body design still includes a measurement of its performance and an investigation of its effect on modem life. The aim of the project is to create a car body concept design tool to achieve the design for fuel consumption, design for aerodynamic noise and design for car body vibration. The system is developed with two options for the user: partial limited function car body design and full function car body design. In the partial limited function design, the user is asked to modify the limited size values on three optimized car body designs; optimum saloon car body design, optimum estate car body design, and optimum hatchback car body design which only took place in the small, local sensitive areas. For the full function car body design, the user is allowed to design the overall automotive's size to create a new outlooking vehicle. In order to do so, databases were created to store information pertaining to size versus fuel, size versus vibration, and size versus noise. As per academic style, the research project begins with the literature review and then concentrates on the survey of the geometry types of existing car body designs. The information has been analyzed and classified to serve as references in building the car body models. It is then tested by using Computational Aero-acoustic (CAA) for noise (dB), Computational Fluid Dynamic (CFD) for fuel economic factors (lift force and drag coefficient), and Finite Element Analysis (FEA) for vibration (Hz). At this stage, all the information from simulation tests are collected and inputted into the database. At the same time, a Taguchi tool is employed to select the optimum BPNN architecture with Genetic Algorithm (GA) which is used to train the BPNN. Finally, the thesis will deliver the car body design modules for estate, saloon and hatchback types with complete information pertaining to external aerodynamic noise, aerodynamic vibration and fuel consumption
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available