Applications of Sequential Quadratic Programming to the Optimization of Powertrain Concept Design

PET (Powertrain Engineering Tool) [1, 2] is based on an object-oriented hierarchy system and therefore each component (parent) has its own sub-component (child) systems. Developing explicit forms of objective functions and constraints is simple due to the object-oriented component system of PET. This system automatically recognizes the geometry of components and related design functions in its sub-component levels. This paper discusses computational efficiency, solution accuracy and robustness of software when using closed-form representatives of the derivatives of objective functions and constraints in sequential quadratic programming. Examples of generating closed-form representatives of the derivatives of objective functions and constraints in C/FORTRAN language syntax by using a symbolic processor, Mathematica [3], and mass reduction of the piston-pin are also presented.