5 results on '"Din, Zakiud"'
Search Results
2. Active Power Decoupling Control for PWM Converter Considering Sensor Failures
- Author
-
Xiong, Jian, Zhang, Jianzhong, Xu, Zheng, Din, Zakiud, and Zheng, Yeming
- Abstract
The power converters integrated with active power decoupling (APD) may handle the ripple power in dc link and then reduce the volume of the filter capacitor dramatically. Generally, voltage and current signals of the LC branch are required for the closed-loop APD control. However, sensor failures could degrade the control performance and even lead to the breakdown of the converter system. This article proposes a detection method for sensor failures in the APD circuit of the single-phase converter. The voltage and current of the LC branch in the APD circuit are estimated by a dual sliding mode observer (SMO). The residuals of the estimated and measured signals are calculated, and they have high sensitivity to specific sensor faults, namely, the current residual is sensitive to the fault of the current sensor and the voltage residual is sensitive to the fault of the voltage sensor, which could be employed to locate the faulty sensors. Finally, the effectiveness of the proposed method is verified by the simulation and experimental results.
- Published
- 2023
- Full Text
- View/download PDF
3. Control of Free Piston Stirling Linear Generator system connected with dc/dc converter for energy storage applications based on SVPWM Rectification Method
- Author
-
Ali, Murad, Haitao, Yu, Che, Zhiyuan, and Din, Zakiud
- Abstract
Recently, the world has been facing several challenges in terms of environmental change, which is expected to increase in the coming periods. Further challenging is how to reduce the emissions of greenhouse gasses into the atmosphere. Such emissions pollute our atmosphere, resulting in global warming. However, the wide use of renewable energies can both help to fight against this phenomenon and reach long-term goals. Considering the growing global concern over the use of fossil fuels and environmental pollution. In this case, a Stirling engine with diversified heat sources and low pollution was developed, and the Free Piston Stirling Linear Generator (FPSLG), which can be directly connected to the Stirling engine and thus eliminate the need for an intermediate mechanical transmission mechanism, was used to create a power generation system with the Stirling engine and has been employed in a range of applications, including space power supply, solar energy generation, and others. This article models two sets of power converters, one of which is connected to the FPSLG and the other to the storage battery system. The Space Vector Pulse Width Modulation (SVPWM) control methods adaption to the AC/DC rectifier and the two-loop Proportional Integral (PI) control method adaption to the DC/DC converter used for renewable energy conversion is proposed. Furthermore, the traditional PI in the position loop is replaced by a Proportional Resonance (PR) controller to increase the frequency and displacement tracking performance. The linear generator’s control system is simulated, and the efficiency of the proposed control strategy is proven. The system was initially simulated in MATLAB/Simulink using the dq-PI current controller to produce the logic pattern for the Voltage Source Rectifier (VSR), and the resulting logic pattern was examined.
- Published
- 2022
- Full Text
- View/download PDF
4. Overmodulation Operation of Hybrid Modular Multilevel Converter With Reduced Energy Storage Requirement
- Author
-
Zhang, Jianzhong, Zhang, Yaqian, Deng, Fujin, and Din, Zakiud
- Abstract
The hybrid modular multilevel converter (MMC) has the advantages of dc fault blocking and overmodulation capability as the promising candidate in future multiport HVdc systems. Especially, the overmodulation ability could increase the modulation index higher than 1 without voltage distortions on the ac side. However, the hybrid MMC under the overmodulation operations could suffer from the voltage deviations between the half-bridge submodule (HBSM) and full-bridge submodule (FBSM) capacitors. In this article, the structure of the self-balancing branches (SBBs) is introduced into the hybrid MMC to eliminate the aforementioned voltage deviations. As a result, the energy storage requirement (ESR) of the hybrid MMC under the overmodulation operations could be greatly reduced compared with the conventional hybrid MMC without SBBs. Besides, the voltage balancing strategy is improved to avoid the impulse current in the conduction path of the SBB, by which the current stress of the power devices could be decreased significantly. The simulations and experiments are carried out to verify the effectiveness of the proposed hybrid MMC. It shows that the ESR of the hybrid MMC could be reduced by 30% with decreased power losses under the overmodulation index 1.5 compared with the conventional hybrid MMC.
- Published
- 2022
- Full Text
- View/download PDF
5. Open switch fault diagnosis of cascade H-bridge multi-level inverter in distributed power generators by machine learning algorithms
- Author
-
Ali, Murad, Din, Zakiud, Solomin, Evgeny, Cheema, Khalid Mehmood, Milyani, Ahmad H., and Che, Zhiyuan
- Abstract
In recent years, multi-level inverters have had remarkable applications in renewable energy sources, high voltage, and other high-power applications. The multi-level inverter has advantages like minimum harmonic distortion and can operate on several voltage levels. A multi-level inverter is being utilized for multipurpose applications such as transportation, communication, industrial manufacturing, aerospace active power filter, Static Var Compensator, and machine drive. Power electronics equipment reliability is very important, and to ensure a multi-level inverter system’s stable operation; it is important to detect and locate faults as quickly as possible. It is difficult to diagnose a fault in a multi-level inverter using a mathematical model because it consists of many switching devices, in this context and to improve fault diagnosis accuracy and efficiency of a cascaded multi-level inverter (CHMLI), a fault diagnosis strategy based on the probability principal component analysis (PPCA) might be utilized. Different machine learning algorithms are used to classify and diagnose the faults under different conditions in a cascaded H-bridge multi-level inverter (CHMLI). This paper presents the comparison of two different machine learning algorithms, such as support vector machine (SVM) and k-Nearest neighbors algorithm (k-NN), based on probabilistic principal component analysis (PPCA) for the effective open switch fault diagnosis in CHMLI employed in distributed generator units. PPCA is a useful technique used for optimizing and data processing without changing the input data’s original properties and characteristics. Using the phase shift pulse width modulation technique, the output voltage signals under different switching fault conditions if the CHMLI are taken as fault features. Both algorithms are used to identify and locate the fault under different modes in CHMLI of distributed generator units. The proposed fault diagnosis methods are compared using simulations and experimental results employing a field-programmable gate array (FPGA) controller. The developed system’s simulation and experimental results perform satisfactorily to detect the fault type, fault location, and reconfiguration. The fault diagnosis time using PPCA-SVM as a fault diagnosis tool for the simulation and experimental case is 0.065 ms and 2.12 ms, respectively. On the other hand, 347 ms and 415 ms fault diagnosis time for simulation and experimental case, respectively, are recorded for the PPCA-kNN based fault diagnosis technique. Therefore, the SVM-based fault diagnosis method is much more efficient and accurate than the k-NN based fault diagnosis method. Moreover, the proposed SVM-based fault diagnosis guaranteed high reliability for CHMLI.
- Published
- 2021
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.