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Automobile transmission design as a constraint satisfaction problem: modelling the kinematic level

Published online by Cambridge University Press:  27 February 2009

Bernard A. Nadel and
Jiang Lin
Bernard A. Nadel
Affiliation:
Computer Science Department, Wayne State University, Detroit, MI 48202, U.S.A.
Jiang Lin
Affiliation:
Computer Science Department, Wayne State University, Detroit, MI 48202, U.S.A.
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Abstract

This paper describes our preliminary results in applying constraint satisfaction techniques in a system we call TRANS-FORM for designing automatic automobile power transmissions. The work is being conducted in collaboration with the Ford Motor Company Advanced Transmission Design Department in Livonia, Michigan. Our current focus is on the design of the mechanical subsystem, but we anticipate extending this later to the electrical and hydraulic subsystems also. For simplicity, in the initial work reported here we restrict ourselves to the relatively well-explored class of transmissions having four forward speeds and one reverse speed, built from two planetary gearsets, cross-connected by two permanent links. Moreover, we pursue design of such transmissions only at the ‘kinematic level’. These two restrictions correspond to limiting respectively the breadth (generality) and the depth (detail or granularity) of the search space employed. We find that, at least for the restricted version of the problem pursued here, transmission design is an application very naturally formulated as a constraint satisfaction problem. Our present problem requires only 10 variables, with an average of about seven values each, and 43 constraints—making it similar in difficulty to about the 10-queens problem. So far, two of the classic transmissions, known as Axod and HydraMatic, have been rediscovered (at the kinematic level) by our program. Preliminary results also indicate that the constraint satisfaction framework will continue to remain adequate and natural even when the search space is allowed to be much broader and deeper. We expect that searches of such expanded spaces will soon lead to the discovery of totally new transmissions.

Information

Type
Research Article
Information
AI EDAM , Volume 5 , Issue 3 , August 1991, pp. 137 - 171
Copyright
Copyright © Cambridge University Press 1991

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