EV Applications Research Articles

A Review on the Fault-Tolerant Method of PMSM using Finite Element Method by Modifying Phase Angle for EV Applications

Abstract: The present research reviews a fault-tolerant technique for Permanent Magnet Synchronous Motors (PMSMs) that involves phase angle adjustment. Fault tolerance standards for the motor used in electric vehicles are necessary due to the rapid development of these vehicles. The primary option for electric vehicle drive motors is increasingly being replaced with permanent magnet synchronous motors (PMSM), which have minimal torque ripple, great durability, and other benefits. After comparing a six-phase PMSM to a conventional three-phase PMSM, the performance following a phase open is examined. A fault-tolerant technique for modifying the left phase current's phase angle to reduce torque ripple following a phase open is then described. The finite element simulation indicates that the six-phase PMSM's output torque ripple is reduced, and the fault-tolerant technique that is being described can further reduce the torque ripple.

Optimized fractional order PID controller with sensorless speed estimation for torque control in induction motor

With rising concern on environmental protection, the exploitation of EV has been widely focused. The IM is said to be the best in comparing varied electric motors for EV applications due to its lower price and robustness. In addition, sensor-less controlling schemes like DTC and FOC are found to be appropriate for crucial appliances owing to their energy savings, improved efficiency, and reliability. The “Optimized Fractional Order Proportional Integral Controller (FoPID)” with a sensor-less speed estimate mechanism is proposed in this work. Additionally, the parameters of FoPID are adjusted using a brand-new hybrid method called the Wolf based Elephant Herding method (W-EHA), which combines the ideas of Grey wolf optimization (GWO) model and Elephant herding optimization (EHO). The superiority of the recommended technique is finally shown in terms of controller performance and error. The RMSE obtained by the developed model at speed = 100 is 3.344, which is 53.89 %, 24.22 %, 1.09 %, and 38.96 % superior to existing approaches like P-controller, MFI-DA + FoPID, EHO-FoPID, and GWO-FoPID respectively.

Artificial intelligence and PI gain optimisation for sensorless indirect vector control of induction motor-based electric vehicle drives

This paper aims to develop indirect vector-controlled induction motor (IM) drives for EV applications. In this paper, controllers are used in two places. The first is the speed controller, used to reduce the error between reference speed and actual EV speed. And the second one is the speed estimator used to reduce the error between the adaptive model and reference model during sensorless operation. The performance of these controllers is compared by using ANFIS, ANN and PI controllers. The real-time performance of the IM-based EV drive system is dependent on the PI gain value. Hence in this paper, seven human and nature-inspired metaheuristic optimisation techniques such as JFO, GWO, ABC, PSO, GA, TLBO and DE are used to obtain the optimised value of the PI controller.

Sustainable Integration of Green Hydrogen in Renewable Energy Systems for Residential and EV Applications

The surge in interest surrounding renewable energy stems from concerns regarding pollution and the finite supply of nonrenewable resources. Solar PV and wind hybrid renewable energy systems (HRES) are increasingly recognized as practical and cost-effective solutions, particularly in remote areas. However, the intermittent nature of solar and wind power presents a challenge. To address this, incorporating a hydrogen source into the system has been proposed. This study focuses on modelling and sizing a hybrid energy system tailored for remote areas, accommodating both home and electric vehicle loads. The simulation is conducted for Siliguri, West Bengal, India, with the goal of optimizing productivity, minimizing expenses, and considering economic factors using HOMER Pro software. The integration of green hydrogen-based power generation with photovoltaic and wind HRES emerges as an effective solution. Solar power, in particular, showcases promising opportunities for the electrolysis process and HRES systems. The presented work facilitates the modelling of a green hydrogen-based green energy system, taking into account capacity, cost, and emission constraints. Various case studies are conducted to enhance system efficiency and reduce the costs of energy (COE). In this paper, three cases of grid-connected and three cases of off-grid or grid-disconnected systems are considered for highlighting the benefits of hydrogen energy incorporation in both types of systems. This research contributes to sustainable energy solutions, advancing a greener and more efficient energy landscape, especially in addressing the recent development in load combinations of home and electric vehicle loads in both grid-connected as well as grid-disconnected system.

Investigation of non-isolated dual-input step-up DC–DC converter using sliding mode control for EV application

Investigation of non-isolated dual-input step-up DC–DC converter using sliding mode control for EV application

Application of Tilt Integral Derivative for Efficient Speed Control and Operation of BLDC Motor Drive for Electric Vehicles

This study presents the tilt integral derivative (TID) controller technique for controlling the speed of BLDC motors in order to improve the real-time control of brushless direct current motors in electric vehicles. The TID controller is applied to the considered model to enhance its performance, e.g., torque and speed. This control system manages the torque output, speed, and position of the motor to ensure precise and efficient operation in EV applications. Brushless direct current motors are becoming more and more popular due to their excellent torque, power factor, efficiency, and controllability. The differences between PID, TID, and PI controllers are compared. The outcomes demonstrated that the TID control enhanced the torque and current stability in addition to the BLDC system’s capacity to regulate speed. TID controllers provide better input power for BLDC (brushless DC) drives than PI and PID controllers do. Better transient responsiveness and robustness to disturbances are features of TID controller design, which can lead to more effective use of input power. TID controllers are an advantageous choice for BLDC drive applications because of their increased performance, which can result in increased system responsiveness and overall efficiency. In an experimental lab, a BLDC motor drive prototype is implemented in this study. To fully enhance the power electronic subsystem and the brushless DC motor’s real-time performance, a test bench was also built.

Fuzzy Logic Controller Based Charging and Discharging Control for Battery in EV Applications

The present research addresses the fuzzy charging and discharge control method for batteries made with lithium-ion utilized in EV applications. The proposed fuzzy-based solution takes into account available parameter to charge or discharge the store within the safe functioning area. To analyses and control battery performance, a variety of controlling methods have been used, but each has its own set of drawbacks, such as the inability to stop two charging conditions, the difficulty of the controller, the lengthy charge time. Due to the lack of mathematical calculations, a fuzzy controller is also simpler to construct, has less additional sensing components, and fewer deep discharging and overcharging protections, making it more efficient in terms of speed and complexity. The effectiveness of the suggested charging-discharging controller system is demonstrated through numerical simulations employing load demand and generation. Performance of the suggested controller is evaluated under simulated load conditions. The model's ability to regulate battery charging and discharging is confirmed by the trial's successful conclusion. The output shows that the battery's state of charge (SOC) never goes above the 20% to 80% safe range for that specific type. A new fuzzy model and an operational real-time system for regulating battery charging and discharging are the major results of this research.

Modified direct torque control algorithm for regeneration capability of IM driven electric vehicle by using hybrid energy storage system

The direct torque control (DTC) algorithm of a 3-phase voltage source inverter (VSI) has been implemented to drive induction motor (IM) for EV applications. However, the conventional DTC for IM is distressed due to large torque ripple, high current total harmonic distortion, and variable switching frequency. So, in this manuscript, a modified direct torque control (MDTC) algorithm is proposed to tackle the said challenges. A three-level hysteresis controller is proposed in modified DTC to optimize the duty ratio of the fundamental voltage vector to minimize the error between the reference and final voltage vector imposed on IM terminals. To improve the efficiency of the EVs by developing a system that uses the energy produced during regenerative braking. The proposed method recovers electric energy produced by the EV without using any additional power converter. The switching patterns allow power flow in both directions. Later, a hybrid energy storage system (HESS) is integrated to supply and store the energy in an optimal way. Extensive studies have been performed to show the efficacy of the proposed MDTC technique in IM based EV application with HESS. The key findings indicate that the proposed MDTC provides better dynamic and steady-state performance.

Optimization of a 12-Slot/10-Pole, Asymmetrical, Six-Phase IPM Considering Healthy and Open-Phase Fault Post Operation in EV Applications

Optimization of a 12-Slot/10-Pole, Asymmetrical, Six-Phase IPM Considering Healthy and Open-Phase Fault Post Operation in EV Applications

Performance analysis of solid-state batteries in Electric vehicle applications

In recent years solid-state batteries, have emerged leading research focus, due to their distinct advantages over conventional batteries. Solid-state batteries, having solid electrolytes, offer higher energy and power density, enhanced safety features and longer lifespan. This makes them ideal in fulfilling demand for energy storage in electric vehicle, and smart grid applications. This study aims to evaluate various types of solid-state batteries, analysing their properties, advantages, and disadvantages, assessing their viability in EV applications. The objective is to identify and recommend the most effective solid-state battery that aligns with the specific demands and operational conditions of electric vehicles and conduct a comprehensive analysis of anode and cathode elements of one of the solid-state batteries in their fresh and damaged state using scanning electron microscopy (SEM).

Minimum Inductor Current Tracking in DAB-based Isolated DC/DC Converter for Q Control with Harmonic Analysis Approach Employing FOGI Filter for EV Applications

Minimum Inductor Current Tracking in DAB-based Isolated DC/DC Converter for Q Control with Harmonic Analysis Approach Employing FOGI Filter for EV Applications

Optimum reference current generation for switched reluctance motor torque ripple minimization in electric vehicle applications.

In this paper, an optimization approach for generating reference current to minimize torque ripple in SRM for EV applications was proposed. Initially, a speed/current controller was developed using the backstepping approach, taking into account magnetic saturation. To generate an optimal current profile, control parameters were optimized using an offline method based on the PSO algorithm. The proposed control strategy was validated using the MATLAB-Simulink environment. A comparison with fixed excitation method was conducted to demonstrate the superiority and robustness of the proposed controller. It achieved reductions in both torque and current ripples of 33.71% and 27.41% respectively. These significant reductions highlighted the proposed controller’s effectiveness, particularly when applied to a driving cycle, and highlighted its overall advantages.

30kW Bidirectional Inductive Power Transfer Charger with Intermediate Coil for EV Applications

30kW Bidirectional Inductive Power Transfer Charger with Intermediate Coil for EV Applications

A Single-Stage Boost Derived Switched-Capacitor- Based PFC Converter for EV Applications

A Single-Stage Boost Derived Switched-Capacitor- Based PFC Converter for EV Applications

Simplified Power Decoupling Control of Triple Active Bridge Converter in Polar Coordinate System for EV Application

Simplified Power Decoupling Control of Triple Active Bridge Converter in Polar Coordinate System for EV Application

Acoustical Noise Mitigation in Slip Angle Controlled DTC of Open-End Winding Induction Motor Drive Using AISPWM Based Triple Randomization Scheme for EV Application

Acoustical Noise Mitigation in Slip Angle Controlled DTC of Open-End Winding Induction Motor Drive Using AISPWM Based Triple Randomization Scheme for EV Application

A Universal-Input On-Board Charger Integrated Power Converter for Switched Reluctance Motor Drive Based EV Application

A Universal-Input On-Board Charger Integrated Power Converter for Switched Reluctance Motor Drive Based EV Application

Neural Network based Direct Torque Controller of SRM for EV Application

Neural Network based Direct Torque Controller of SRM for EV Application

Module Voltage and Resistance Estimation of Battery-Integrated Cascaded Converters through Output Sensors Only for EV Applications

Module Voltage and Resistance Estimation of Battery-Integrated Cascaded Converters through Output Sensors Only for EV Applications

Bridgeless SEPIC PFC Converter for Low Voltage EV Applications With Reduced Sensor Count

Bridgeless SEPIC PFC Converter for Low Voltage EV Applications With Reduced Sensor Count