Analysis, Modeling and Neural Network Traction Control of an Electric Vehicle without Differential Gears

Abstract

This paper presents system analysis, modeling and simulation of an EV with two independent rear wheel drives. The traction control system is designed to guarantee the EV dynamics and stability in case of no differential gears. Using two electrics in-wheel motors give the possibility to have a torque and speed control in each wheel. This control level improves the EV stability and the safety. The proposed traction control system uses the vehicle speed, which is different from wheels speed characterized by slip in the driving mode, an input. In this case, a generalized neural network algorithm is proposed to estimate the vehicle speed. In terms of the analysis and the simulations carried out, the conclusion can be drawn that the proposed system is feasible. Simulation results on a test vehicle propelled by two 37-kW induction motors showed that the proposed control approach operates satisfactorily.