Otimização Paramétrica Veicular Via Algoritmos Genéticos
DOI:
https://doi.org/10.19142/rpq.v14i28.616Keywords:
parametric optimization, powertrain, vehicle, genetic algorithmAbstract
This work presents an application of genetic algorithms in an automotive vehicle to search for optimum engine speed parameters used in gear changes in order to optimize fuel economy and acceleration performance from 0 to 100 km/h. Standardized FTP and HWFET fuel economy tests were considered. The optimization sought three direction profiles: a global optimization, a specific optimization that disregards the HWFET test and one that disregards the FTP test. The results were compared to a typical driving profile with gear changes at 3000 rpm and gear reductions at 1000 rpm. The global optimization solution achieved 11.55% improvement in FTP fuel economy, but there was a 14.30% reduction in HWFET fuel economy. The solutions found by AG in the specific optimizations achieved improvements of 13.71% in fuel economy in the FTP test and 1.53% in fuel economy in the HWFET test. In all the optimizations, improvements were made in the time from 0 to 100 km/h of up to 3.79%. The results showed that the genetic algorithm managed to obtain good results in the specific optimizations.
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