Journal of Controller and Converters

Wireless Power Transfer System for Electric Vehicle Charging

Pandurang Pujari — 2024-12-05

The design and development of a Wireless Power Transfer (WPT) system that does not require wires or plugs for Electric Vehicle (EV) charging is presented in this study. The proposed system utilizes magnetic resonance coupling technology to transfer power between a transmitter coil embedded in the ground and a receiver coil integrated into the EV. The system operates at a frequency of 85 kHz and can deliver up to 3.7 kW of power with an efficiency of 90%. The WPT system consists of a transmitter unit, a receiver unit, and a control unit. The transmitter unit comprises a high-frequency inverter, a transmitter coil, and a compensation network. The receiver unit consists of a receiver coil, a rectifier, and a DC-DC converter. The control unit ensures efficient power transfer and safety features. Experimental results demonstrate the system's feasibility and efficiency, paving the way for convenient and automated EV charging. The proposed WPT system offers a promising solution for future EV charging infrastructure, enhancing user experience and promoting widespread adoption of eco-friendly transportation. This technology eliminates the need for physical connections, reducing wear and tear on components and improving user convenience. The core of WPT systems involves resonant inductive coupling, where an alternating current generates a magnetic field in a primary coil, which then induces a current in a secondary coil located in the EV.

Railway Health-Monitoring Using KSK Approach: Decision-Making Using AIIoT Approach in Railways

Kazi Kutubuddin Sayyad Liyakat — 2024-10-23

The application of ML algorithms that can interpret massive amounts of data collected by sensors is at the core of this approach to Artificial Intelligence (AI) and the Internet of Things (IoT). These algorithms can recognize trends and irregularities that may indicate wear and tear or early failures in essential systems. By way of illustration, vibration sensors installed on trains can identify abnormalities in wheel dynamics, while track-side monitoring systems are able to check for the condition of the track. By incorporating these insights into a centralized health monitoring platform, railway operators are not only able to comprehend the present state of health of their assets, but they are also able to make well-informed decisions regarding the scheduling of maintenance and the distribution of resources. Furthermore, the novel utilization of edge computing inside this AIIoT framework makes it possible to do data processing at the local level, hence lowering latency and enabling quick reactions to highly urgent circumstances. In a railway context, where rapid interventions can decrease the likelihood of accidents and increase the dependability of service, this is of the utmost importance Furthermore, coupling AI and IoT with cloud computing opens up chances for advanced data analytics and machine learning models. These models have the potential to continuously improve their accuracy over time as additional data becomes accessible. In essence, this innovative approach to the Internet of Things not only improves operational efficiency but also coincides with broader programs that aim to make rail transportation more environmentally friendly by minimizing the number of routine maintenance visits that are not essential and maximizing the utilization of resources. The choice made by the system is based on the state of the track, the train's speed, and the train's condition on the authority.

Speed Control of BLDC Motor using PID Controller by using MATLAB

N. S. Jadhav — 2024-12-21

The Brushless DC (BLDC) motor has become a widely used electrical machine in various applications due to its high efficiency, reliability, and precise control capabilities. Speed control of BLDC motors is crucial in systems requiring accurate and dynamic performance. This paper proposes using a PID (Proportional-Integral-Derivative) controller to regulate the speed of a BLDC motor in real-time. The PID controller is designed to minimize the error between the desired and actual motor speed, thereby improving system stability and performance.

MATLAB/Simulink is used to model and simulate the BLDC motor system, with the PID controller implemented to adjust the motor's speed based on feedback from the motor's actual speed. The motor dynamics, including the back EMF (Electromotive Force) and phase current control, are considered for an accurate simulation. The system's performance regarding speed response, steady-state error, and transient behavior is analyzed. The results show that the PID controller effectively reduces the speed error and provides good tracking of the reference speed, demonstrating the potential of this approach for precise motor control in practical applications. This approach contributes to the field of motor control by presenting a simple yet effective method for real-time speed regulation, with the ability to fine-tune the controller's parameters to suit different application requirements.

Clamper Circuit using Matlab

N. S. Jadhav — 2024-11-21

In this paper, models for both negative and positive clamper circuits were developed, simulated, and analyzed. Simulation results indicated that the required series capacitance was directly proportional to the duty cycle and the input signal’s period for the negative clamper circuit. In contrast, for the positive clamper circuit, the series capacitance was inversely proportional to the duty cycle while remaining directly proportional to the signal period. The parallel resistance required for the negative clamper circuit was inversely proportional to the duty cycle. In contrast, the positive clamper circuit was directly proportional to the duty cycle of the input signal. These models were validated using Simscape, with results showing consistency across simulations. The modeling and simulations were conducted in MATLAB.

IoT-Powered Dynamics for Smart DC Motor Control

S. H. Shete — 2024-12-23

Motor control involves initiating, guiding, and regulating purposeful voluntary movements. This entails the body's or system's capability to initiate, direct, and adapt movements to carry out specific actions efficiently. For example, when someone reaches out to pick up an object, the brain sends signals to the muscles to initiate and control that movement. According to Shumway-Cook, a well-known researcher in motor control, it involves the ability to adapt mechanisms essential for movement. This means motor control is not just about producing movements but also adjusting and fine-tuning those movements based on external and internal factors. For instance, while walking on uneven terrain, the body continuously adapts muscle responses to maintain balance and stability. This bidirectional motor driving system utilizes the widely recognized dual H-Bridge motor driver Integrated Circuit (IC). The term "bidirectional" indicates that the system allows motors to move in both forward and reverse directions. The IC is widely used because it is reliable, efficient, and a foundational component for controlling motor movement. The H-Bridge design is a key feature that enables motors to operate in multiple directions by controlling current flow. The circuit allows you to easily control motors independently, handling currents of up to 2A in each direction. In technical terms, the circuit design ensures that two motors can be controlled simultaneously and independently, meaning each motor can move at its speed and direction without interfering with the other. The capability to handle up to 2A of current per motor makes it suitable for medium-power motors in projects such as robots or automated systems.