Pemanfaatan Baterai untuk Mengurangi Beban Puncak dan Meningkatkan Penyerapan Energi Regenerative Braking pada Kereta Api

Semakin meningkatnya kebutuhan transportasi dan meningkatnya pemanasan global akibat polusi, maka sistem transportasi massal merupakan alternative utama. Kereta api merupakan salah satu moda transportasi yang paling effisien dari segi energi dibandingkan moda transportasi lain. Kereta api listrik merupakan kereta yang ramah lingkuangan. Akan tetapi, kereta ini memerlukan energi listrik yang besar. Salah satu cara untuk mengurangi konsumsi energi kereta listrik adalah dengan regenerative braking. Listrik hasil regenerative braking kurang dapat termanfaatkan dan kebanyakan dibuang di brake resistor. Energy Storage System (ESS) dapat dipakai untuk menyimpan energi hasil regenerative braking. ESS dapat diletakkan disamping lintas (track-side) maupun pada sarana kereta api (on-board). ESS on-board (ESS-OB) memiliki efisiensi dan manajemen energi yang lebih mudah. Baterai dipilih menjadi ESS-OB karena marupakan salah satu jenis ESS yang lebih unggul dibanding tipe lain yaitu flywheel dan super-capacitor. Pengujian simulasi dilakukan dengan memodelkan substasiun, kereta api, ESS-OB, dan brake resistor. Pada pengujian kereta berjalan diantara dua substasiun dan berhenti di tiga stasiun kereta api. Hasil pengujian menunjukkan bahwa penambahan baterai sebagai ESS-OB di kereta mampu menyerap energi hasil regenerative braking dengan baik dan mampu mengurangi beban puncak hingga 2,11 %. Penghematan energi akan lebih banyak jika diterapkan pada beberapa unit kereta dan frekuensi perjalanan yang lebih tinggi. Penambahan baterai ini juga meningkatkan massa kereta hingga 0,07%

Speed Control of Induction Motor using LQG

The electric motor is one of the technological developments which can support the production process. Not only in the manufacturing, but also in the transportation sector. The AC motor is divided into the synchronous and asynchronous motor. One type of asynchronous motor which widely used is the induction motor. In this study, the application of the IFOC control method and the LQG speed control method will be used to control the speed of an induction motor. The PID algorithm is also used as a comparison. Tests were carried out using MATLAB software. The speed variation and load variation are tested to validate the controller performance. PID is superior in terms of settling time and IAE. On the other hand, LQG is better in energy consumption. In terms of IAE, LQG has a higher value compared to PID by up to 56.67%. On the other hand, LQG is superior in terms of energy, which is 8.38% more efficient

Prototipe Automatic Feeder dengan Monitoring IoT untuk Perikanan Bioflok Lele

Revolusi Industri 4.0 telah banyak membawa banyak perubahan baik itu positif maupun negartif. Segi positifnya yaitu telah banyak dipakainya otomasi dan robot di dunia industri sehingga produksi bisa meningkat pesat. Sedangkan sudut negatif, semakin banyaknya pekerjaan manusia yang tergantikan oleh mesin sehingga memperkecil peluang kerja. Adanya revolusi industri 4.0 juga membawa kesenjangan antara kelompok melek teknologi dan kelompok gagap teknologi (gaptek). Warga kampung atau desa merupakan kelompok besar dari golongan gaptek. Untuk itu, suatu peluang usaha baru yang dapat dikerjakan msyarakat desa dengan tingkat pendidikan menengah sangat diperlukan. Maka dipilihlah program perikanan bioflok lele. Sentuhan teknologi otomasi dan Internet of Things (IoT) diberikan untuk meningkatkan produktivitas dan membuat masyarakat melek akan perkembangan teknologi era revolusi industry 4.0

Fuzzy-PID in BLDC Motor Speed Control Using MATLAB/Simulink

Brushless DC motors (BLDC) are one of the most widely used types of DC motors, both in the industrial and automotive fields. BLDC motor was chosen because it has many advantages over other types of electric motors. However, in its application in the market, most of the control systems used in BLDC motors still use conventional controls. This conventional method is easy and simple to apply but has many weaknesses, one example is that if the system state changes, then the parameters of the PID must also be changed so that static and dynamic performance will decrease, causing slow response and frequent oscillations. In this study, the design and simulation of a speed control system for BLDC motors using the Fuzzy-PID method were carried out. The research method is performed through simulation with Matlab / Simulink. The simulation is carried out by providing a speed setpoint input of 650 rpm and used 2 methods, namely Fuzzy-PID Logic and Pi conventional method which was carried out for 1 second. The test results show that the Fuzzy-PID control can provide better and more stable performance than the conventional PI control. The use of Fuzzy-PID control can reduce speed fluctuation and torque stability so that the BLDC motor can operate more efficiently and reliably

POSITION CONTROL OF VTOL SYSTEM USING ANFIS VIA HARDWARE IN THE LOOP

Electric motors have been widely applied in various equipment. One application is found in Unmanned Aerial Vehicles (UAVs). An electric motor speed control system that can balance the aircraft's position is one of the mandatory features that must be owned by the aircraft. The position balancer control also supports the Vertical Take-Off Landing (VTOL) system. This study's VTOL position control system uses Hardware-in-the-loop (HIL) method with MATLAB Simulink and Arduino. ANFIS (Adaptive Neuro-Fuzzy Inferences System) is used as a position control algorithm. The controller performance is compared with conventional PID and FLC (Fuzzy Logic Controller). The system is tested as an initial position variation and loading test. The experiment shows that HIL can help fast prototyping by faster changes in the controller algorithms and is easy to program. The result is varied in each experiment. In the ISE (Integral Square of Error) point of view, ANFIS is better than PID by 100 % and has a very small difference from FLC in the initial position test. ANFIS is better by 95.44% and 4.56% compared with PID and FLC in the loading test, respectively

Design and Prototyping of Electronic Load Controller for Pico Hydropower System

A hydroelectric power plant is an electrical energy generator that utilizes water energy to drive a water turbine coupled to a generator. The main problem in hydroelectric power plants is the frequency and voltage fluctuations in the generator due to fluctuations in consumer loads. The purpose of this research is to make a prototype of the Electronic Load Controller (ELC) system at the Pico Hydropower Plant. The main part of ELC is the frequency sensor and gating system. The first part is made by a Zero Crossing Detector, which detects the generator frequency. The gating system was developed with TRIAC. The method used is the addition of a complement load which is controlled by delaying the TRIAC. Load control is intended to maintain the stability of the electrical energy produced by the generator. The PID algorithm is used in frequency control. The results of the frequency sensor accuracy test are 99.78%, and the precision is 99.99%. The ELC system can adjust the frequency automatically by setting the firing delay on the TRIAC to distribute unused power by consumer loads to complementary loads so that the load used remains stable. The ELC is tested with increasing and decreasing load. The proposed ELC gives a stable frequency at 50Hz. Whereas at the first test, the mean voltage is 183V, and in the second test is 182.17V

Hybrid fuzzy-PID like optimal control to reduce energy consumption

The electric motor is one of the appliances that consume considerable energy. Therefore, the control method which can reduce energy consumption with better performance is needed. The purpose of this research is to minimize the energy consumption of the DC motor with maintaining the performance using Hybrid Fuzzy-PID. The input of the Fuzzy system is the error and power of the system. Where error is correlated with matric Q and power is correlated with matric R. Therefore, adjusting the fuzzy rule on error and power is like adjust matrices Q and R in LQR method. The proposed algorithm can reduce energy consumption. However, system response is slightly decrease shown from ISE (Integral Square Error). The energy reduction average is up to 5.58% while the average of ISE increment is up to 1.89%. The more speed variation in the system, the more energy can be saved by the proposed algorithm. While in terms of settling time, the proposed algorithm has the longest time due to higher computation time in the fuzzy system. This performance can be increased by tuning fuzzy rules. This algorithm offers a solution for a complex system which difficult to be modeled

Design and Application of PLC-based Speed Control for DC Motor Using PID with Identification System and MATLAB Tuner

Industries use numerous drives and actuators, including DC motors. Due to the wide-ranged and adjustable speed, DC motor is widely used in many industries. However, the DC motor is prone to external disturbance and parameter changes, causing its speed to be unstable. Thus, a DC motor requires an appropriate controller design to obtain a fast and stable speed with a small steady-state error. In this study, a controller was designed based on the PID control method, with the controller gains tuned by trial-and-error and MATLAB Tuner with an identification system. The proposed controller design was implemented using PLC OMRON CP1E NA20DRA in the hardware implementation. Each tuning method was repeated five times so that the system performances could be compared and improved. Based on hardware implementation results, the trial-error method gave acceptable results but had steady-state errors. On the other hand, the use of MATLAB Tuner provided fast system responses with no steady-state error but still had oscillations with high overshoot during the transition. Therefore, the PID controller gains acquired from MATLAB Tuner must be tuned finely to get better system responses