RT-LAB Platform for Real-Time Implementation of Luenberger Observer Based Speed Sensorless Control of Induction Motor

Bechar, Mansour; Hazzab, Abdeldjebar; Habbab, Mohamed; Sicard, Pierre; Slimi, Mohammed

doi:10.14313/jamris/4-2019/39

Cited by 1 publication

(1 citation statement)

References 14 publications

(13 reference statements)

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“…In RT-LAB, each computation subsystem is assigned to a different core. In other words, each subsystem is coded in C and built for execution among its processors using Mathworks code generator Real-Time-Workshop (RTW) [ 43 ]. After compilation, the code is loaded into target OP5700 via TCP/IP protocol and executed via parallel processing.…”

Section: Real-time Platform Using Rt-labmentioning

confidence: 99%

Model Predictive Direct Torque Control and Fuzzy Logic Energy Management for Multi Power Source Electric Vehicles

Kakouche

Rekioua

Mezani

et al. 2022

Sensors

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This paper proposes a novel Fuzzy-MPDTC control applied to a fuel cell battery electric vehicle whose traction is ensured using a permanent magnet synchronous motor (PMSM). On the traction side, model predictive direct torque control (MPDTC) is used to control PMSM torque, and guarantee minimum torque and current ripples while ensuring satisfactory speed tracking. On the sources side, an energy management strategy (EMS) based on fuzzy logic is proposed, it aims to distribute power over energy sources rationally and satisfy the load power demand. To assess these techniques, a driving cycle under different operating modes, namely cruising, acceleration, idling and regenerative braking is proposed. Real-time simulation is developed using the RT LAB platform and the obtained results match those obtained in numerical simulation using MATLAB/Simulink. The results show a good performance of the whole system, where the proposed MPDTC minimized the torque and flux ripples with 54.54% and 77%, respectively, compared to the conventional DTC and reduced the THD of the PMSM current with 53.37%. Furthermore, the proposed EMS based on fuzzy logic shows good performance and keeps the battery SOC within safe limits under the proposed speed profile and international NYCC driving cycle. These aforementioned results confirm the robustness and effectiveness of the proposed control techniques.

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Section: Real-time Platform Using Rt-labmentioning

confidence: 99%