Determination of Maximum Possible Fuel Economy of HEV for Known Drive Cycle: Genetic Algorithm Based Approach

This paper describes a methodological approach to investigate the maximum fuel economy that could be achieved by a hybrid vehicle with parallel configuration for a known drive cycle. A backward looking hybrid vehicle model is used for computation of fuel economies. The optimization process represents a constrained, multi-domain and time-varying problem, which is highly nonlinear. Here, genetic algorithm (GA) based approach was used to find out optimum power split between two power sources over their driving cycles that make maximum possible overall fuel economy for the given drive cycle by the vehicle. In this approach using Parallel Hybrid Electric Vehicle (PHEV) configuration, optimization problem is formulated so as to minimize the overall fuel consumption. The whole set of electric motor power contribution along the drive cycle is then coded as the chromosomes. These results represent the maximum fuel economy that could be ever achieved by any power management system of a Hybrid Electric Vehicle, with the tested HEV configuration and shall allow setting a benchmark against which the fuel economy is measured.