Browsing by Author "Premasiri, R. H. M. D."

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Comparison of different methods for generating SPWM signal for the development of a pure Sine wave inverter
(Faculty of Science, University of Kelaniya Sri Lanka, 2023) Hemal, S. B. N. H.; Dilshan, G. K. D.; Karunarathna, M. A. D. D. S.; Morawakaarachchi, K. N.; Senanayake, S. V.; Premasiri, R. H. M. D.; Piyumal, P. L. A. K.; Ranaweera, A. L. A. K.
An inverter is an electronic device which is used for converting Direct Current (DC) to Alternating Current (AC) because AC is the predominant form of electrical power used in homes, businesses, and most electrical appliances. Inverters can be categorized based on the type of waveform that they produce, such as Pure Sine Wave Inverters, Modified Square Wave Inverters and Square Wave Inverters. This paper discusses the development of a Pure Sine Wave Inverter with an output voltage of 230 VRMS and a frequency of 50 Hz using the Sinusoidal Pulse Width Modulation (SPWM) technique. Three SPWM signal generation methods, including analogue comparator, microcontroller, and SPWM driver module methods, were tested. This study presents a method to obtain a 230 VRMS, 50 Hz output sine wave in three steps. The first step involves the generation of an SPWM signal with frequency control, utilizing the DC source supply. The analogue comparator method uses op-amps as the analogue comparator. Then, it compares a reference sinusoidal wave with a high-frequency (in kHz range) carrier triangular wave. The output of the op-amp comparator is SPWM. The frequency of this reference sinusoidal wave is chosen based on the required inverter output frequency (50 Hz). In that process, the comparator gives out a pulse when the voltage of the sine waveform is greater than the triangular voltage, and this pulse is used to trigger the respective inverter switches. When designing a circuit that involves op-amps, the slew rate of the op-amp is a critical consideration. To generate an SPWM signal using an ATmega328p microcontroller, the microcontroller was used to generate a series of PWM signals by digital high and digital low. The corresponding time of each pulse's delay is added using the microsecond function. Increasing and decreasing duty cycle, and then a series of PWM signals. As the pure sine wave inverter SPWM driver module EGS002 was used and, that method was the more accurate method, and a clean SPWM signal was generated with less harmonics. Although this type of inverter board has more features, the circuitry was not complex because of the module. Secondly, we employ the MOSFET H-bridge stage to obtain the desired sine wave output. Finally, the third step focuses on supplying a high DC voltage to the H-bridge circuit, which the DC-DC PWM boost converter generates. Several circuit protections were included to ensure the device's safety and reliability. In the process of SPWM generation, although in the analogue comparator method, op-amps offer a low-cost option, a microcontroller is favoured for its superior precision and ability to handle high-power applications effectively. However, the EGS002 module stands out as the preferred method due to its user-friendly nature, comprehensive protection features, and ability to provide valuable feedback, making it a more economically efficient choice in the overall design.
Development of a cost-effective real-time commuter counting system for public transportation in Sri Lanka
(Faculty of Science, University of Kelaniya Sri Lanka, 2023) Premasiri, R. H. M. D.; Koralage, K. G. S. D.; Hasaranga, J. P. K.; Alawaththa, A. K. N. A.; Seneviratne, J. A.; Ranaweera, A. L. A. K.
The use of smart systems in public transportation is relatively new in the Sri Lankan context. This study introduces a cost-effective solution for accurately counting the number of bus passengers at any given time. Current passenger counting systems in Sri Lanka often suffer from inaccuracies and inefficiencies, hindering the effective management of public transportation and addressing problems including long bus queues, ticketing fraud, long waiting times, etc. Precise passenger count is essential for optimising services and resources, ultimately enhancing the efficiency of public transportation in the country. The proposed system is designed to be installed in buses and includes an online platform where users can enter the bus number and check the passenger occupancy in real-time. The proposed system comprises several key components: two input sensors, a microcontroller, a wireless connectivity module, an in-built display, an input panel, and an output display. The two sharp IR sensor modules employed as input sensors are connected to a microcontroller. An inbuilt display connected to the microcontroller provides output information, including passenger count, number of vacant seats, GPS signal strength, and data transmitting capability. Data is wirelessly sent to a cloud database for storage, retrieval, and processing, enabling users to access relevant information via a web application. The algorithm employed in this system ensures precise passenger count by detecting specific sequences of readings from the two IR sensors. To increment the passenger count, the system requires the following sequence: "0-0, 1-0, 1-1, 0-1, 0-0." This sequence corresponds to the detection of a passenger boarding the bus. Each step in the sequence represents the state of the two IR sensors, with "0" indicating no obstacle and "1" indicating an obstacle (i.e., the presence of a passenger). The algorithm recognizes this sequence as an entry event and increments the passenger count accordingly. Conversely, the algorithm relies on the following sequence to accurately decrease the passenger count when a passenger exits the bus: "0-0, 0-1, 1-1, 1-0, 0-0." This sequence represents a passenger leaving the bus. The algorithm reduces the passenger count by monitoring the sensor readings and identifying this sequence. These specific sequences in the algorithm ensure reliable and accurate passenger counting. By requiring a particular order of sensor readings, false positives or negatives caused by noise or temporary obstacles are minimised, leading to a more precise passenger count. The online platform allows users to access passenger occupancy in a particular bus, which aids in real-time service optimization for public transportation management. The system achieves precise real-time passenger occupancy tracking using two Sharp IR sensors and a finely tuned algorithm. Tested results of the pilot system show that data empowered public transportation management in Sri Lanka by optimising routes, efficiently allocating resources, and significantly improving the overall commuter experience. In conclusion, the combination of affordability, reliability, and user-friendliness makes this proposed solution suitable for efficiently managing public transportation systems.
Investigation of MPPT in photovoltaic systems with step-down DC-DC converter and supercapacitor energy storage
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Premasiri, R. H. M. D.; Piyumal, P. L. A. K.; Ranaweera, A. L. A. K.; Kalingamudali, S. R. D.
This study explores the implementation of Maximum Power Point Tracking (MPPT) in photovoltaic (PV) systems integrated with a step-down DC-DC converter and supercapacitor (SC) based energy storage. The integration of renewable energy sources, particularly solar power, necessitates highly efficient energy conversion and storage mechanisms to maximise the utility of the harvested energy. MPPT techniques play a pivotal role in optimising the power output of PV systems by dynamically adjusting the operating point to extract the maximum possible power under varying environmental conditions. SCs, with their high charge and discharge rates and high power density, emerge as a promising storage solution to manage the intermittent and variable energy output characteristic of PV systems. A Constant Voltage (CV) MPPT algorithm is employed to fine-tune the power output and ensure maximum energy efficiency. The experimental setup comprises a Solar Array Simulator simulating the PV array, interfaced with a step-down DC-DC converter, and an SC configured as the load. The system's performance is analysed by observing the available, actual and output power using a power analyser and evaluated to ascertain the robustness and effectiveness of the MPPT algorithm. The research distinguishes itself by utilising SCs as the primary load, an approach not commonly adopted in previous studies. Few studies have investigated the use of SCs exclusively as the load, and those that have indicated that MPPT is not efficiently achieved under such conditions. However, the analysed results affirm that the system proficiently tracks the maximum power point, attaining an average MPPT efficiency of 94.88% when the system is integrated with the CV MPPT algorithm. The average conversion efficiency attained was 75.62% with a basic DC-DC step-down converter constructed on a solderless board. It is anticipated that this MPPT efficiency will further improve with the application of more sophisticated MPPT algorithms such as Perturb and Observe (P&O), Incremental Conductance (IncCond), and Hill Climbing (HC). The average conversion efficiency can be increased by fine-tuning the converter and implementing more advanced topologies of DC-DC stepdown converters. This research makes a substantial contribution to advancing high-efficiency and dependable PV energy storage systems, underscoring the practical viability of SCs as an energy storage device. Furthermore, these findings have significant implications for SC-assisted Heating, Ventilation, and Air Conditioning (HVAC) systems integrated with PV systems, where efficient MPPT can enhance overall system performance as MPPT can be tracked when using the SC as the storage. Prospective studies will examine the long-term stability and scalability of this innovative approach in larger-scale PV installations, paving the way for more resilient and efficient renewable energy systems.
IoT-enabled intelligent pedestrian crossing signal light system with violation tracking
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Rupasinghe, R. A. I. M.; Ranasinghe, R. A. J. B.; Moragoda, Y. G. D.; Navodya, W. D. I.; Premasiri, R. H. M. D.; Chethana, E. J. K. S.; Seneviratne, J. A.; Gunawardana, K. D. B. H.
The urban pedestrian crossing environment presents numerous challenges in ensuring the safety of pedestrians and maintaining smooth traffic flow. Traditional pedestrian signaling systems operate on fixed timings and have limited capabilities, making it difficult to manage the complexities of modern urban traffic effectively. This research introduces an innovative system for pedestrian crossing signal lights integrated with violation tracking and real-time data analytics to improve pedestrian safety and smooth traffic flow. This encompasses computer vision for pedestrian detection, machine learning (ML) for predictive analysis, adaptive signal light timers, sirens for violation deterrence, and IoT components for seamless real-time operation. The presented methodology combines real-time pedestrian detection, adaptive signal light timing, weather detection, and IoT integration so that all these subsystems work smoothly. The issues resolved include integrating image processing with hardware, selecting an efficient pedestrian detection model, optimizing camera angles for accurate detection, and transitioning from an Arduino to a Raspberry Pi 4 Model B. The Raspberry Pi offered better processing power, enabling faster and more complex data handling. A case study was done at a location proximate to the University of Kelaniya, and the average crossing time taken for the pedestrian crossing was recorded as 18.5 seconds, which can be factored using databases with larger data sets and simple ML models based on the day of the week. The issues that were resolved include integrating image processing with hardware, selecting an appropriate pedestrian detection model such as a Convolutional Neural Network (CNN) that works well within the outdoor environment, setting optimal camera angles for accurate pedestrian detection, and transitioning from an Arduino to a Raspberry Pi 4 Model B for enhanced processing capabilities. Integrating image processing with hardware posed challenges due to the need for real-time data transmission and processing, which required seamless communication between the software and hardware components. The pedestrian detection model was chosen based on its accuracy, speed, and ability to perform well in varying lighting and weather conditions. The transition to the Raspberry Pi 4 Model B, with its superior processing power and memory compared to the Arduino, allowed the system to handle more complex tasks, such as real-time data analysis and multiple input streams, significantly improving performance and efficiency. A custom dataset of overhead views of pedestrians was created, with images acquired from a similar environment within the university, manually labelling the images and achieving an 80% accuracy after training on Google Collab. The real-time data processing system is vital in making dynamic signal timing changes, tracking violations to encourage safe pedestrian behavior, and managing pedestrian and vehicle traffic flow. These findings endorse the broader adoption of intelligent systems, for innovative city projects toward safer and more efficient urban environments.