Improved hybrid DTC technology for eCAR 4-wheels drive

Njock Batake Emmanuel Eric, Nyobe Yome Jean Maurice, Ngoma Jean Pierre, Ndoumbé Matéké Max

Abstract


This article deals with the design of a hybrid controller (HyC). It combines fuzzy logic (FL), adaptive neuro-fuzzy inference system (ANFIS). It is combined with direct torque control (DTC). This HyC-DTC combination is designed to improve the technical performance of a 04-wheel drive electric vehicle (EV). A stress test is identically applied to the DTC combined with the FL (FDTC) and to the HyC-DTC in order to certify the suitability of this new control following a cross-validation. This is based on dynamic stability criteria (overshoot, rise time, accuracy), analysis of torque and flux oscillations, and the EV's robustness symbol. The EV's magnetic quantities are managed by a master-slave module (VMSC). Simulations are carried out using MATLAB/Simulink software. The HyC-DTC achieves near-zero accuracy like the FDTC, with overshoot around 0.2% less than the FDTC, and torque oscillation amplitude around 4 times less than the FDTC. However, its rise time is 0.045% greater than that of the FDTC. It is therefore slower, but more precise and suitable for EV transmission systems in terms of safety and comfort.

Keywords


direct torque control; electric vehicle; electronic differential; induction motor; neuro-fuzzy

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DOI: http://doi.org/10.11591/ijpeds.v16.i3.pp1566-1585

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