Powertrain Hybridization and Parameter Optimization Design of a Conventional Fuel Vehicle Based on the Multi-objective Particle Swarm Optimization Algorithm

Recently, the hybridization of the conventional fuel vehicle has attracted extensive attention among the automotive industry and related research institutions to meet increasingly rigorous fuel consumption (FC) regulations and emissions. This article introduces a hybridization design and parameter optimization methodology to transform a conventional fuel powertrain into the biaxial hybrid one. To utilize this hybrid powertrain, an energy management strategy (EMS) is proposed based on the rule-based control strategy which determines torque distribution between the engine and the motor according to the engine optimal FC area. To achieve better fuel economy, an off-line optimization of both control parameters and powertrain parameters is conducted using the multi-objective particle swarm optimization (MOPSO) algorithm. The research on the fuel economy potential of this hybrid powertrain, corresponding EMS, and parameters optimization are carried out through simulation. The results show that fuel economy improvement of 29.96% and 20.75% along the New European Driving Cycle (NEDC) and Worldwide harmonized Light Vehicle Test Procedure (WLTP) could be achieved.