Improved hybrid DTC technology for eCAR 4-wheels drive

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.

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Publication Details

Journal
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Published
2025-09-01
DOI
https://doi.org/10.11591/ijpeds.v16.i3.pp1566-1585
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
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article

Improved hybrid DTC technology for eCAR 4-wheels drive

Ndoumbè Matéké Max, Nyobe Yomé Jean Maurice, Njock Batake Emmanuel Eric, Ngoma Jean Pierre
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Electric and Hybrid Vehicle Technologies
article

Improved hybrid DTC technology for eCAR 4-wheels drive

Ndoumbè Matéké Max, Nyobe Yomé Jean Maurice, Njock Batake Emmanuel Eric, Ngoma Jean Pierre
article en

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.

International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer EngineeringVol. 16(3)
University of Douala (CM)
Openalex Percentile: Top 75%
Electric and Hybrid Vehicle Technologies
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