Research Papers: Design Theory and Methodology

Simulation-Based Computational Design Synthesis Using Automated Generation of Simulation Models From Concept Model Graphs

[+] Author and Article Information
Clemens Muenzer

Engineering Design and Computing Laboratory,
Department of Mechanical and
Process Engineering,
ETH Zurich,
Tannenstr. 3,
Zurich CH-8092, Switzerland
e-mail: muenzerc@alumni.ethz.ch

Kristina Shea

Engineering Design and Computing Laboratory,
Department of Mechanical and
Process Engineering,
ETH Zurich,
Tannenstr. 3,
Zurich CH-8092, Switzerland
e-mail: kshea@ethz.ch

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received July 7, 2016; final manuscript received April 1, 2017; published online May 12, 2017. Assoc. Editor: Andy Dong.

J. Mech. Des 139(7), 071101 (May 12, 2017) (13 pages) Paper No: MD-16-1491; doi: 10.1115/1.4036567 History: Received July 07, 2016; Revised April 01, 2017

Current approaches in computational design synthesis (CDS) enable the human designer to explore large solution spaces for engineering design problems. To extend this to support designers in embodiment and detail design, not only the generation of solution spaces is needed but also the automated evaluation of engineering performance. Here, simulation methods can be used effectively to predict the behavior of a product. This paper builds on a general approach to automatically generate solution spaces for energy and signal-based engineering design tasks using first-order logic and Boolean satisfiability. The generated concept model graphs (CMGs) are now in this paper automatically transformed into corresponding bond-graph-based simulation models. To do this, guidelines for creating partial simulation models for the available synthesis building blocks are presented. The guidelines ensure valid causality in the final simulation model. Considering the connections in the concept model graphs, the simulation models are automatically generated and simulated. The simulation results are then used to calculate different objectives, constraints, and performance metrics. The method is validated using automotive powertrains as a case study. One hundred and sixty-two different powertrain concepts are generated and evaluated, showing the advantages of electric powertrains with respect to CO2 emissions and the importance of considering intelligent control strategies in the future for hybrid ones.

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Fig. 1

CDS process overview [11]

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Fig. 2

Bond-graph constituents and their causalities

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Fig. 3

Example taxonomy of flow-ports

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Fig. 4

A connection between a clutch and a gearbox as an example for elements and their connections. Throughout this paper, the in-ports are always located on the left-hand side, and the out-ports always on the right-hand side of the element.

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Fig. 6

Compatibility issues between two elements of one kind and their solution

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Fig. 7

Scheme of the implementation of the proposed method. Apart from “metamodel” and “solution space,” the white boxes represent used third party software, and the gray boxes represent scripts, extensions, and software that was developed for this paper.

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Fig. 10

Graph symbol and partial simulation model. The dashed gray lines illustrate the mapping between the connectors in the simulation model and the ports in the graph model.

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Fig. 11

System boundary for hybrid powertrains and its' partial simulation model. At the bottom of the simulation model, the cumulated error ei is calculated.

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Fig. 12

Complete solution space

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Fig. 13

Solution space excerpt with selected solutions ranging from three to six components

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Fig. 14

Speed profiles for the exemplary CMGs. The dotted lines indicate the given speed profile. The solid lines indicate the actual speed profiles.

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Fig. 15

Hybrid powertrain CMG containing ten components (for illustration purposes, the relations connecting signal ports are colored gray, and those connecting energy ports are colored black)

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Fig. 16

The hybrid powertrain CMG (for illustration purposes, the relations connecting signal ports are colored gray, and those connecting energy ports are colored black) similar to the Toyota Prius and its simulated NEDC speed profile. The dotted lines indicate the given speed profile. The solid lines indicate the actual speed profile.




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