Optimization of an automotive generator using evolutionary programming

One of the primary design requirements of automotive generation systems is maximizing power density subject to the constraint of minimizing overall system cost. However, with progress made in reduction of automotive drive train noise, the torque ripple of the generator has been found to be a dominant noise source under idle conditions at high electrical load. Thus, an added design constraint is the minimization of torque ripple produced by the machine. In order to meet these objectives, numerical tools have been developed to automate the design process. A primary tool is an evolutionary algorithm that has been integrated within a customized magnetic equivalent circuit based model of the machine. In this paper, a description of the optimization procedure is provided, along with results that demonstrate its use in selecting optimal rotor pole geometry.