Idriss Benlaloui

The growing demand for electric vehicles (EVs) has driven research into improving propulsion control systems, focusing on performance, efficiency, and safety. This study addresses a gap in advanced control systems for EV differentials and presents two solutions. First, an innovative electric power steering (EPS) filter algorithm is introduced, drawing inspiration from mechanical steering systems. Second, a newly designed fuzzy logic controller (FLC) is presented. This controller utilizes the vehicle's measured speed and turning angle to control dynamics and stability. These solutions aim to regulate speed and steering angle to enhance stability at high speeds, improve user comfort, and minimize the risk of sliding or overturning. To validate and compare these approaches, three propulsion control configurations for an EV with dual permanent magnet synchronous motors (PMSMs) using field‐oriented control (FOC) were simulated in MATLAB‐Simulink under a Federal Test Procedure (FTP 75) signal. These strategies include: (1) an EV without differential gears using a classical electric differential (CED), (2) an EV with the proposed EPS filter algorithm to regulate speed and steering angle, and (3) an EV incorporating a new fuzzy controller to improve stability and safety by controlling the driver‐input angle. Performance analysis focused on motor speed, torque, and differential speed. The CED setup served as a baseline, while the EPS filter was assessed for cornering stability, and the fuzzy controller for smoother torque distribution and reducing motor speed differences. This comparative study highlights the strengths and weaknesses of each strategy, offering insights into their impact on EV performance and stability. Results show that the EPS filter enhances cornering stability, while the fuzzy controller ensures smoother torque distribution and reduces motor speed differences. These contributions optimize EV propulsion systems, improving performance and safety.

This paper addresses the challenges of coil misalignment in wireless inductive power transfer (WIPT) systems for electric vehicle (EV) battery charging, focusing on static wireless charging (SWC) performance. It evaluates the impact of lateral and vertical misalignments on circular and rectangular coil designs with ferrite cores, using detailed electromagnetic simulations in Ansys Maxwell. The system efficiency of these geometries was subsequently calculated and analyzed using Ansys Simplorer to provide an integrated electromagnetic–circuit co‐simulation approach. The study demonstrates how much ferrite cores enhance magnetic coupling. Research demonstrates that circular coils exhibit greater resilience to angular misalignments when paired with series–series (S–S) compensation compared to the rectangular coils. These findings provide new insights into optimizing WPT system design for misalignment tolerance, justifying the inclusion of circular coils alongside SAE‐J2954‐recommended rectangular coil designs for specific applications. The study concludes that combining circular coils with ferrite‐assisted S–S compensation provides a higher efficiency and misalignment‐resilient design for EV charging.

Interest in wind turbine emulators (WTE) has increased due to the growing need for wind power generation as a low-maintenance, more effective substitute for conventional models. This paper presents the design of a small WTE utilizing a dSPACE 1104 system. The setup includes a DC motor, driven by a buck converter, coupled to a permanent magnet synchronous generator, all managed through a hardware-in-the-loop configuration using the dSPACE 1104 board. The DC motor simulates the rotational motion generated by wind energy, accurately replicating the characteristics of an actual WT. This control system enables the simulation of various wind speeds and torque values in MATLAB/Simulink software, providing a valuable tool for analyzing and developing power converters. The results obtained confirmed the effectiveness of the proposed emulator, as the experimental outcomes closely matched the theoretical calculations.

This article proposes a new method to diagnose intern-turn short-circuit (ITSC) faults in the stator winding of an induction motor (IM). The ITSC faults change stator winding resistance values, which can be estimated in real time using a model reference adaptive system (MRAS). However, estimation of the stator resistance in the stationary reference frame may not provide accurate information when an incipient ITSC fault occurred in a given phase. As a result, the classical MRAS is limited to detecting symmetric ITSC faults and cannot detect asymmetric ones. To overcome this limitation, a novel approach based on the differences between the measured stator currents in motor phases and the estimated currents obtained from an IM model is proposed. These differences are multiplied by estimated stator currents and used to develop an adaptive mechanism using proportional integral (PI) regulators in each motor phase. To ensure stability, Popov’s criterion inequality is used in the adaptive rule design method. The proposed approach is stable and capable of detecting and estimating different levels of ITSC, including asymmetric faults, in various motor operating modes. The effectiveness of the proposed approach was verified through simulation and experimental results.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose’s challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems. Emulation offers a promising alternative due to financial constraints, spatial limitations, and climate dependency in full-scale systems. The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. Precise induction motor control is achieved through a controlled inverter. This work innovatively combines PV and WP emulation while optimizing system dynamics, aiming to develop a comprehensive emulator and evaluate an enhanced control algorithm. An optimized scalar control strategy regulates the water MP, demonstrated through MATLAB/Simulink simulations that highlight superior performance and responsiveness to solar irradiation variations compared to conventional MPPT techniques. Experimental validation using the dSPACE control desk DS1104 confirms the emulator’s ability to faithfully reproduce genuine solar panel characteristics.

The increasing demand for electric vehicles (EVs) is driven by the urgent need for environmentally friendly transportation. This paper addresses the challenge of optimizing EV drivetrain efficiency by proposing a novel single-inverter electronic differential system for distributed EV drivetrains. The research focuses on reducing system cost and complexity while maintaining high performance. The methodology involves a detailed simulation using MATLAB/Simulink to validate the theoretical soundness of the proposed connection method. The results demonstrate that the proposed system achieves a minimum accuracy rate of 97.5%, marking a significant improvement over traditional dual-inverter systems. This approach not only enhances drivetrain efficiency but also contributes to more compact and cost-effective vehicle designs. Additionally, the findings underscore the potential for further refinement and exploration, suggesting that continued advancements in ED systems could lead to even greater performance gains in the future. This research lays the groundwork for future innovations in EV technology, particularly in the areas of cost reduction and system efficiency.

Hybrid renewable energy systems (HRES) integrating solar, wind, and storage technologies offer enhanced efficiency and reliability for grid-connected applications. However, existing control methods often struggle with maintaining DC voltage stability and minimizing power fluctuations, particularly under variable load conditions. This paper addresses this research gap by proposing a novel control strategy utilizing a PD (1+PI) regulator that combines proportional–integral (PI) and proportional–derivative (PD) controllers. Integrated into the HRES with maximum power point tracking (MPPT), the system includes solar panels, a storage unit, and a wind system featuring a permanent magnet synchronous generator (PMSG). The PD (1+PI) regulator plays a critical role in stabilizing DC voltages within the storage system and collaborates with predictive direct power control (P-DPC) to improve current quality by mitigating fluctuations in active and reactive power. Comparative analysis against traditional direct power control methods shows that the proposed strategy reduces voltage fluctuation by 30% and improves energy utilization efficiency by 25%, validating its efficacy in managing energy from diverse sources to meet nonlinear load demands. The results demonstrate that integrating the PD (1+PI) regulator with MPPT and P-DPC approaches enhances power stability and optimizes energy utilization in grid-connected HRES, underscoring the effectiveness of this advanced control system.