Among issues facing the transportation sector today is the limited autonomy of electric vehicles, which are highly reliant upon energy storage systems. Considering this issue as the current research gap, researchers seek to prolong vehicle dependability through renewable-free and sustainable energy that tackles negative environmental impacts. This research exploits the electric vehicle’s kinetic energy to improve its performance and reliability. It uses fuel-cell resources and supercapacitors hybridized with lithium-ion batteries, in addition to DC generators connected to front wheels that convert their rotations into energy contributing to the vehicle’s overall power balance. A state machine-based energy management strategy computes fuel-cell setpoint power, while a dual-loop structure uses a super-twisting controller for DC bus voltage regulation and recovery, in addition to tracking banks’ setpoint currents. A speed controller-based artificial intelligence is proposed to reduce power losses and enable accurate tracking of running trajectory to improve vehicle mechanisms. The simulation results using Matlab Simulink software proved the proposed vehicle’s feasibility by adopting the free kinetic energy of additional DC generators that provided 28% of its total power requirements, resulting in superior supply efficiency reaching 98%. Thus, the stress on FC and battery was minimized by 21% and 10%, respectively, in addition to reducing fuel consumption by 39%, so the vehicle autonomy was extended, and its reliability was enhanced and supported, as targeted.

This paper compares different maximum power point tracking (MPPT) control strategies in microgrid dynamics, focussing on perturb and observe (P&O), adaptive neuro-fuzzy inference system (ANFIS), particle swarm optimisation (PSO), and PSO sliding mode controller techniques. The study investigates their performance under varying microgrid conditions, considering factors like weather and load variations. The simulation results provide a detailed comparative analysis of the power at the point of common coupling (PCC) for MPPT techniques at different time intervals. Both the P&O and PSO sliding mode recorded a power output of 287 kW, while PSO-ANFIS achieved a slightly higher power output of 294 kW. At 2.5 seconds, the P&O method recorded a power output of 712 kW, while the PSO sliding mode and the PSO-ANFIS techniques achieved 717 kW and 738 kW, respectively. Overall, the PSO-ANFIS technique consistently outperformed the other methods in terms of power output, demonstrating its effectiveness in maximising energy extraction and adaptability to dynamic conditions. These findings provide valuable insights for designing and implementing MPPT controllers in microgrid systems, emphasising the efficiency of the hybrid PSO-ANFIS technique in enhancing the overall performance and stability of renewable energy systems.

The field of energy is of great interest for development, especially in the transportation industry. This paper investigates a hybrid electric vehicle (HEV) with two-wheel drives powered by a fuel cell, battery, DC generators, and supercapacitors. Each energy source is connected to a specific controllable converter. The authors compared the energy management strategies of the Adaptive Neuro-Fuzzy Inference System (ANFIS) with classical energy management strategies. The proposed ANFIS method reduced hydrogen consumption by 8% compared to the classical approach, and improved efficiency to over 98%. The primary objective of this work is to demonstrate the impact of artificial intelligence in renewable energy management strategies (EMSs), with the aim of improving system performance as much as possible by comparing it with classical methods such as state machine (SM) and PI strategies.

In this paper, PV arrays are connected to the grid through a three-Level NPC Inverter. Both the current control and voltage balancing performance of the inverter are ensured via model predictive control (MPC) technique. This paper is comparing and presenting operational performance analysis of grid-connected three-Level NPC Inverter results using three techniques controllers namely: Self-tuning Fuzzy Logic PI controller (FLC), Neural Network controller (ANN), and PI classical controller, under different environmental conditions to optimally tune the reference current of the controller and following the maximum power point.

This paper provides an experimental analysis of a non-linear load-based disturbed system. The shunt hybrid power filter is proposed to avoid propagating the non-linear load-based harmonic current and giving compensation for reactive power. shunt hybrid power filter is a combination of a small-rating active power filter and a passive 5th, 7th harmonic tuned LC filter. In order to control a power shunt hybrid filter to minimize the total harmonic distortion, we use active and reactive instant power theory. In this article, we use the controller PI control technique in the first section and the second part, we use the flow logic and mode control sliding through the device, and we compared a theme. The output of shunt hybrid filter in reducing harmonic distortions and compensating for reactive power is defined in the experimental results. Through this research paper, we conclude that this type of hybrid filter had a significant role in reducing the THD ratio from 29 to 3.7

Many modern electric vehicles use hybrid energy storage systems, which combine multiple energy sources. Because of their rapid charge and discharge cycles, high power densities, longer lifespans than batteries, and resistance to stress, supercapacitors (SCs) are the best option for HESS when combined with batteries. In order to improve the independence of electric vehicles, SCs are used as energy storage devices during sudden power changes and to recover braking energy. In this paper, a speed management strategy is implemented to improve the performance of electric scooters by providing the necessary power from load and power recovery during braking or counter-load. This tactic relies on a so-called ON/OFF control technique to measure the SC and battery's power sharing. To evaluate the effectiveness of the electric scooter's control strategy and the system's energy management under varying loads, a MATLAB/Simulink model has been created. The findings demonstrate that using a super capacitor alleviates the electrical strain placed on the battery