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Journal : Mechatronics, Electrical Power, and Vehicular Technology

Design and Implementation of Anti-windup PI Control on DC-DC Bidirectional Converter for Hybrid Vehicle Applications Romdlony, Muh. Zakiyullah; Amin, Amin
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 3, No 1 (2012)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (884.259 KB) | DOI: 10.14203/j.mev.2012.v3.31-38

Abstract

Well-regulated DC bus voltage is the important point to guarantee the power demand in hybrid vehicle applications. Voltage regulation can be achieved with control method that build switching signal on DC-DC converter. This paper describes design and small scale experimental results of bus voltage regulation control of the DC-DC bidirectional converter with battery and supercapacitor as energy source. The control system consists of two control loops, the outer loop that get DC bus voltage feedback using PI anti-windup back calculation control method. This outer loop will generate a reference current for the inner loop that implement hysteresis control. The inner control loop will compare that reference curent with the source current obtained from the current sensor. Simulation and experimental results show that bus voltage is well-regulated under the load changes with 1% voltage ripple.
Hardware-in-the-loop simulation of DC motor as an instructional media for control system design and testing Muhammad Zakiyullah Romdlony; Fakih Irsyadi
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 12, No 2 (2021)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2021.v12.81-86

Abstract

Instructional media in control systems typically requires a real plant as an element to be controlled. However, this real plant, which is costly to be implemented, can be replaced by a virtual plant implemented in a computer and modelled in such a way that it resembles the behavior of a real plant. This kind of set-up is widely termed as hardware-in-the-loop (HIL) simulation. HIL simulation is an alternative way to reduce the development cost. A virtual plant is easy to adjust to represent various plants or processes that are widely used in industry. This paper proposes a simple HIL simulation set-up designed as instructional media for design and testing a simple control system. The experimental result on DC motor control shows that HIL simulation dynamical response is similar to the real hardware response with a small average error on measured transient response, represented in 0.5 seconds difference in settling time and 7.43 % difference in overshoot. This result shows the efficacy of our HIL simulation set-up.
Design and Implementation of Anti-windup PI Control on DC-DC Bidirectional Converter for Hybrid Vehicle Applications Muh. Zakiyullah Romdlony; Amin Amin
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 3, No 1 (2012)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2012.v3.31-38

Abstract

Well-regulated DC bus voltage is the important point to guarantee the power demand in hybrid vehicle applications. Voltage regulation can be achieved with control method that build switching signal on DC-DC converter. This paper describes design and small scale experimental results of bus voltage regulation control of the DC-DC bidirectional converter with battery and supercapacitor as energy source. The control system consists of two control loops, the outer loop that get DC bus voltage feedback using PI anti-windup back calculation control method. This outer loop will generate a reference current for the inner loop that implement hysteresis control. The inner control loop will compare that reference curent with the source current obtained from the current sensor. Simulation and experimental results show that bus voltage is well-regulated under the load changes with 1% voltage ripple.
Design and application of models reference adaptive control (MRAC) on ball and beam Muhammad Zakiyullah Romdlony; Muhammad Ridho Rosa; Edwin Muhammad Puji Syamsudin; Bambang Riyanto Trilaksono; Agung Surya Wibowo
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 13, No 1 (2022)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2022.v13.15-23

Abstract

This paper presents the implementation of an adaptive control approach to the ball and beam system (BBS). The dynamics of a BBS are non-linear, and in the implementation, the uncertainty of the system's parameters may occur. In this research, the linear state-feedback model reference adaptive control (MRAC) is used to synchronize the states of the BBS with the states of the given reference model. This research investigates the performance of the MRAC method for a linear system that is applied to a non-linear system or BBS. In order to get a faster states convergence response, we define the initial condition of the feedback gains. In addition, the feedback gains are limited to get less oscillation response. The results show the error convergence is improved for the different sets of the sinusoidal reference signal for the MRAC with modified feedback gains. The ball position convergence improvement of MRAC with modified feedback gains for sinusoidal reference with an amplitude of 0.25, 0.5, and 0.75 are 35.1 %, 36 %, and 52.4 %, respectively.
LSTM-based forecasting on electric vehicles battery swapping demand: Addressing infrastructure challenge in Indonesia Muhammad Zakiyullah Romdlony; Rashad Abul Khayr; Aam Muharam; Eka Rakhman Priandana; Sudarmono Sasmono; Muhammad Ridho Rosa; Irwan Purnama; Amin Amin; Ridlho Khoirul Fachri
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.72-79

Abstract

This article aims to design a model for forecasting the number of vehicles arriving at the battery swap station (BSS). In our case, we study the relevance of the proposed approach given the rapid increase in electric vehicle users in Indonesia. Due to the vehicle electrification program from the government of Indonesia and the lack of supporting infrastructure, forecasting battery swap demands is very important for charging schedules. Forecasting the number of vehicles is done using machine learning with the long short-term memory (LSTM) method. The method is used to predict sequential data because of its ability to review previous data in addition to the current input. The result of the forecasting using the LSTM method yields a prediction score using the root-mean-square error (RMSE) of 2.3079 x 10-6 . The forecasted data can be combined with the battery charging model to acquire predicted hourly battery availability that can be processed further for optimization and scheduling.
Event-triggered robust formation control of multi quadrotors for transmission line inspection Tamba, Tua Agustinus; Cinun, Benedictus Christo Geroda; Nazaruddin, Yul Yunazwin; Romdlony, Muhammad Zakiyullah; Hu, Bin
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 2 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.1106

Abstract

This paper proposes an event-triggered formation control scheme to manage the operation of multiple quadrotors in performing the inspection of a power transmission line. In particular, the problem of controlling such multi quadrotors to track the tower and/or cables of the transmission lines is considered. A multi-agent sliding mode control method is used for this purpose and is equipped with both a radial basis function neural network as an estimator of environmental wind disturbances, as well as an event-triggered scheduling scheme for the control execution framework. The proposed multi quadrotors control method is designed by considering the transmission tower/cable as the reference sliding surface. Simulation results are presented to illustrate the effectiveness of the proposed multi quadrotors control scheme when implemented in a case scenario of tracking the commonly-encountered shape of transmission cables. Simulation results are presented and show how the implementation of a position error-based event-triggered control enables all UAVs to track the desired position and maintain a pre-determined formation. In particular, all UAVs can minimize the tracking error within 0.05 m after reaching the desired positions since the control signal is updated if the error reaches such an error bound.
RHO–LSTM-based optimal scheduling at the motorcycle battery swapping station under battery heterogeneity Fauziah, Nisa Evi; Romdlony, Muhammad Zakiyullah; Muharam, Aam; Yakub, Fitri
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1172

Abstract

This research proposes a mechanism that enables the battery swapping station (BSS) to provide battery swap services for multiple types of batteries, termed battery heterogeneity, utilized in electric motorcycles. The number of batteries for each type is established. The battery charging cost is calculated in real time, and the station's profit is maximized by optimizing battery swap scheduling. The issues are modeled as a mixed-integer non-linear problem (MINLP), then linearized as a mixed-integer linear problem (MILP), using the grid electricity price from the real-time pricing mechanism to calculate the battery's charging/discharging cost. Swap scheduling is optimized using the rolling horizon optimization (RHO) approach, which takes into account a variety of constraints. These constraints include battery type, battery SoC, arrival time of the electric motorcycle, grid electricity pricing at time t, and battery power utilization. The long-short term memory (LSTM) predicts the electric motorcycles' arrival time at t+1 based on prior data. The results show that optimization scheduling generates a higher overall profit per day than unscheduled operation. Profit by the RHO-LSTM method is 23.77 % greater than by the RHO-Polynomial method and 0.26 % greater than by unscheduled operation. Furthermore, the number of batteries provided by the RHO-LSTM method is 40 % greater than by the RHO-polynomial method.