Real-time driving strategy for a pure electric vehicle with multiple traction motors by particle swarm optimization

This paper introduces a real-time torque-distribution driving strategy for a pure electric vehicle. This vehicle is driven by a powertrain of three traction motors: an indirectly-driven traction motor for front wheels and two in-wheel motors installed inside both rear wheels. Their torque distribution is determined by particle swarm optimization theory for minimizing energy consumption according to the torque-speed-efficiency maps of all the traction motors. Simulation results by hardware-in-the-loop show that the driving efficiency of the proposed real-time torque-distribution driving strategy by particle swarm optimization is close to the results from the global optimization method by dynamic programming.