Parametric optimization of novel electric-hydraulic hybrid steering system based on a shuffled particle swarm optimization algorithm

The on-board battery is the primary energy storage device of the electric vehicle that provides power to drive all actuators of the chassis, i.e., the energy consumption of each actuator has a direct impact on the vehicle's energy management system. To reduce energy consumption while steering and improve the handling stability of electric vehicles, a novel electric-hydraulic hybrid steering (E-HHPS) system with multiple steering modes is presented herein. The electric power mode is used to reduce the overall energy consumption of the system by adaptive intervention, whereas the hybrid power mode is responsible for the steering portability in conditions of increased steering torque. To further improve the performance of the E-HHPS system, the structural parameter optimization model of the E-HHPS system is established based on the consideration of the steering economy, steering road feeling, and steering sensitivity. To solve the multi-objective optimization problem with characteristics of increased dimensions, a shuffled particle swarm optimization algorithm (SPSO) is proposed to realize a combination of a local search and global information exchange. The simulation results demonstrate that compared with the EHPS system, the E-HHPS system has a better steering economy at low vehicular speeds. In addition, the E-HHPS system optimized by the SPSO algorithm can considerably reduce the steering energy consumption and noticeably improve the handling performance of the vehicle.