Mohd Rizal Manan
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Preferred name
Mohd Rizal Manan
Official Name
Mohd Rizal , Manan
Alternative Name
Manan, M. R.
Main Affiliation
Scopus Author ID
36514937100
Researcher ID
FKS-3641-2022

Research Output

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  • Publication
    Adaptive PD Controller Performance for Direct Cooling of Thermoelectric Refrigerator
    ( 2020-12-18)
    Mohd Saifizi Saidon
    ;
    Mohd Rizal Manan
    ;
    Baseemah Mat Jalaluddin
    ;
    Junaidah Ali Mohd Jobran
    ;
    Wan Azani Wan Mustafa
    ;
    Roejhan Md Kawi
    ;
    Lee T.W.
    ;
    Mat Piah M.S.
    ;
    Diana N.S.
    Refrigerator is the key component to keep the medicine and biological sample in the hospital. The domestic refrigerator has the problem of larger size and heavier weight since to the compact system like condenser, compressor, evaporator and expansion valve are assemble and using in the refrigerator. This project focused on design of temperature control of the portable thermoelectric refrigerator for medical purpose. Thermoelectric refrigerator is using the direct cooling method through thermoelectric module. Thermoelectric refrigerator has several advantages such as smaller size, lighter and silent when operated. Since maintain a constant temperature for the storage of medical product is important, a specific refrigerator is needed to ensure the medicine is stored in desired temperature. This project is to design and develop an adaptive control system which can perform a good temperature control for the thermoelectric refrigerator. The second order model is applied to design adaptive Proportional-Derivative (PD) controller. The selected controller is the adaptive PD controller because the performance of response shows 0.42 C of less steady state error and 0.21 C of lower undershoot. The adaptive PD control system designed able to let the refrigerator operate in different operating condition without influence the performance of the refrigerator.
  • Publication
    System Design for Early Detection of Explosive and Flammable Gas Leaks Using Mobile Robot in Confined Space
    ( 2021-12-01)
    Muhammad Aizat Abu Bakar
    ;
    Mohd Rizal Manan
    ;
    Roejhan Md Kawi
    ;
    Yunn, L. J.
    The presence of explosive or flammable gases in confined space may contribute towards accidents that threaten the workers safety and industrial progress. Conventionally, the existing instrument for gas detection in confined space is manually carried by humans whereby the workers or competence person itself were exposed directly to the gases. This project is aim to develop a prototype system to detect the presence of gases leak where the robotic system replaces humans to carry gas sensors. Users only need to maneuver the robot using a mobile phone to monitor the specific area that may have an explosive or flammable gas leak which includes Liquefied Petroleum Gas (LPG) and methane gases. The sensors will detect if a change in the gas concentration has exceeded a safety limit and will activate the alarm as an alert signal. The readings of gases as input signals were sent wirelessly to the Personal Computer (PC) as a user device for monitoring purposes. This prototype is successfully developed, tested and calibrated using the samples of LPG gas, methane, smoke and environment temperature. The result proved that the developed system is able to detect an air sample using selected gas sensors and display the data in graph form with live monitoring. This will contribute significantly to acquiring a new and alternative method using the system for detecting the presence of gases in confined space application.
  • Publication
    Fusion wind and solar generation forecasting via neural network
    ( 2021-08-27)
    Mahmoud Mustafa Yaseen Mohammed Al Asbahi
    ;
    Muhammad Naufal Mansor
    ;
    Mohd Rizal Manan
    ;
    Mohd Azri Abd Aziz
    ;
    Roejhan Md Kawi
    ;
    Farah Hanan Mohd Faudzi
    Wind and solar power are the most common renewable resources of energy and their usage for power generation is quickly growing all over the world. However, both wind and solar power are difficult to predict manually due to every time changes in weather condition; therefore. power output of wind and solar is associated with some uncertainty. A reliable wind-solar day ahead load prediction proposed in this paperwork to support a small microgrids system. The system is a combination of hardware of solar panel, wind turbine, hybrid charge controller, current sensor, voltage sensor circuit, battery, Arduino Mega and personal computer that is install with MATLAB along with artificial neural network model for load forecast. The prediction model is known as Feedforward back propagation (FFBP) artificial neural network (ANN), this method utilizes a learning relationship between wind-solar power output and predicted weather. The FFBP model trained ANN to recognize similar pattern and to predict the output power based on train and tested data and the results achieved 99.5 accuracy, 6.25% MAPE and 1.2 % MAD.
  • Publication
    Fusion wind and solar generation prototype design with Neural Network
    ( 2021-08-27)
    Mahmoud Mustafa Yaseen Mohammed Al Asbahi
    ;
    Muhammad Naufal Mansor
    ;
    Mohd Rizal Manan
    ;
    Mohd Azri Abd Aziz
    ;
    Roejhan Md Kawi
    ;
    Farah Hanan Mohd Faudzi
    Wind and solar power are the most common renewable resources of energy and their usage for power generation is quickly growing all over the world. However, both wind and solar power are difficult to predict manually due to every time changes in weather condition; therefore, power output of wind and solar is associated with some uncertainty. A reliable wind-solar day ahead load prediction with neural network was proposed to support a small microgrids system. All the system performance measurement such as sensitivity, specificity and accuracy give higher than 90%.
  • Publication
    A Review on BLDC Motor Application in Electric Vehicle (EV) using Battery, Supercapacitor and Hybrid Energy Storage System: Efficiency and Future Prospects
    ( 2023-04-01)
    Aziz M.A.A.
    ;
    Mohd Saifizi Saidon
    ;
    Fahmi M.I.
    ;
    Othman S.M.
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Rizal Manan
    ;
    Muhammad Zaid Aihsan
    The automotive industry has rapidly introduced pollution-free vehicles such as Electric Vehicle (EV). The development and improvement of the EV to replace the conventional vehicle become crucial to obtain the customer satisfaction and high technology achievements. The main systems in EV that are improvise to be switch from the conventional engine with a fuel source to an electric type drive system, include the electric motor and the energy/power storage called battery. There are several types of electric motors that suitable for EV and the best solution was Brushless Direct Current (BLDC) motor in terms of power, speed, torque and low maintenance. Meanwhile, the fuel source replacement is the electrical energy/power storage such as batteries. The aims were to study the best Energy Storage System (ESS) in EV which leads to introducing Battery Energy Storage System (BESS), but the drawbacks of the system give the opportunity improvement, in replacement using Supercapacitor Energy storage System (SESS) and Hybrid Energy Storage System (HESS). SESS is a reliable source, but the stand-alone Supercapacitor also has a minimum operation time. With several adjustments in the energy management control strategy, the discharge rate of energy from a supercapacitor can be minimized to prolong its operation.