Modified Direct Torque Control of Solar Fed Sensorless Switched Reluctance Motor Drive for Electric Vehicle With Regenerative Braking

Kumar, Arjun; Singh, Bhim; Singh, Gurmeet

doi:10.1109/tia.2023.3330452

Cited by 1 publication

(1 citation statement)

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“…A switched reluctance motor (SRM) is suitable for light EVs, and the torque control (TC) strategy involves no feedback sensor for the rotor position of the SRM. A self-charging capability is not addressed with this control method [23]. A traditional PI controller with solar PV and battery-to-light EVs for power management implemented a reluctance synchronous motor (RSM).…”

Section: Introductionmentioning

confidence: 99%

Novel Machine Learning Control for Power Management Using an Instantaneous Reference Current in Multiple-Source-Fed Electric Vehicles

Mathesh,

Saravanakumar,

Salgotra

2024

Energies

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Using multiple input power sources increases the reliability of electric vehicles compared to a single source. However, the inclusion of other sources exhibits complexity in the controller system, such as computing time, program difficulty, and switching speed to connect or disconnect the input power to load. To ensure optimal performance and avoid overloading issues, the EV system needs sophisticated control. This work introduces a machine-learning-based controller using an artificial neural network to solve these problems. This paper describes the detailed power management control methodology using multiple sources like solar PV, fuel cells, and batteries. Novel control with an instantaneous reference current scheme is used to manage the input power sources to satisfy the power demand of electric vehicles. The proposed work executes the power split-up operation with standard and actual drive cycles and maximum power point tracking for PV panels using MATLAB Simulink. Finally, power management with a machine learning technique is implemented in an experimental analysis with the LabVIEW software, and an FPGA controller is used to control a 48 V, 1 kW permanent-magnet synchronous machine.

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Section: Introductionmentioning

confidence: 99%