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Ong Hui Lin
Preferred name
Ong Hui Lin
Official Name
Ong, Hui Lin
Alternative Name
Ong, Huilin
Ong, H. L.
Lin, Ong Hui
Lin, O. H.
Lin Ong, Hui
Main Affiliation
Scopus Author ID
57189322712
Researcher ID
F-5201-2010
Now showing
1 - 9 of 9
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PublicationBioinspired Crosslinked Nanocomposites of Polyvinyl Alcohol-Reinforced Cellulose Nanocrystals Extracted from Rice Straw with Ethanedioic Acid( 2022-01-01)
;Chin K.M. ;Tan W.K.Vannaladsaysy V.In this study, cellulose nanocrystals (CNC) were extracted from rice straw and incorporated into polyvinyl alcohol (PVOH) as reinforcement nanofillers. Multiple nanocomposites with different CNC contents were prepared. Extracted CNC appear as long, well-defined rodlike crystals with a high aspect ratio (41). Nanocomposites with 3 wt% of CNC significantly exhibit improved tensile strength (60.4%) and maximum degradation temperature (287°C). Moreover, they demonstrate a decrease in water vapor permeability rate and in the swelling and solubility indices of PVOH/CNC. Significant improvements were observed when nanocomposites were crosslinked specifically in terms of tensile strength (104.8%) and maximum degradation temperature (364°C). They also demonstrate greatly reduced water vapor permeability rate, swelling, and solubility indices. The optimum CNC amount for both nanocomposites is 3 wt%. -
PublicationBiodegradation improvement of bioinspired crosslinked and noncrosslinked polyvinyl alcohol nanocomposites with cellulose nanocrystals extracted from rice straw through natural soil burial exposure( 2022-10-01)
;Chin K.M.Tan W.K.Polyvinyl alcohol with different cellulose nanocrystals (CNC) content extracted from rice straw were prepared by using solution casting method and their biodegradability in natural soil burial were studied. Ethanedioic acid (EA) was introduced as a crosslinker. The synthesized noncrosslinked and crosslinked PVOH/CNC nanocomposites films and their biodegradation were characterized with Fourier transform infrared spectroscopy (FTIR), tensile test, weight loss, Field Emission Scanning Electron Microscopy (FESEM), differential scanning calorimetry (DSC). The changes in chemical properties before and after biodegradation were confirmed through FTIR. Tensile test revealed that the tensile strength and elongation at break reduced as time of soil burial increases. Morphological study showed the extent of surface deterioration before and after soil burial, where the addition of CNC displayed greater deterioration. Melting temperature and crystallinity increased with addition of CNC but decreased after crosslinking. However, melting temperature and crystallinity of all nanocomposites increased after biodegradation. PVOH degrading bacteria were isolated and identified to be Bacillus cereus strain CCM 2010 and Bacillus cereus strain ATCC 14579. Biodegradation of the bionanocomposites were concluded to be in the following decreasing order: PVOH/CNC > PVOH/EA/CNC > PVOH > PVOH/EA. -
PublicationInvestigation the optimum performance of the surface-mounted PMSM under different magnetization patterns( 2020-01-07)
;Akmar Mohd-Shafri, Syauqina ;Ishak D. ;Jun Tan C.This paper investigates the influence of different magnetization patterns on the performances of the surface-mounted permanent magnet synchronous machines (SMPMSMs). Three magnetization patterns are employed, which are radial, parallel, and ideal Halbach magnetizations. These magnetization patterns are applied to 9-slot/10-pole and 15-slot/4-pole permanent magnet (PM) machines. The PM machines are designed and simulated by using Opera 2D finite element. The performances of three PM motors, such as airgap flux density, phase back-EMF, and cogging torque, are evaluated under the influence of different magnetization patterns. The total harmonic distortion of phase back-EMF (THDv) for the motors are investigated. The PM motors with ideal Halbach magnetization provide the lowest cogging torque and the lowest total harmonic distortion of phase back-EMF. Besides that, the optimum setting of the magnet pole-arc can reduce the total harmonic distortion of phase back-EMF and achieve lower cogging torque. The optimum magnet pole-arc produced by radial magnetization in 9-slot/10-pole motor is 24.8 mech., with cogging torque of 0.45 Nm, and THDv of 2.69 %. Meanwhile, the optimum magnet pole-arc produced by parallel magnetization in 9-slot/10-pole motor is 26.0 mech., with cogging torque of 0.41 Nm, and THDv of 2.00 %. -
PublicationOptimization Design of the Electromagnetic Torque for Surface-Mounted PMSM Using GA and Finite Element Analysis for Electric Vehicle( 2022-09-01)
;Wong E.W.M. ;Mohd-Shafri S.A. ;Tan C.J. ;Ishak D. ;Leong J.H.This research offers an optimization design for a three-phase surface-mounted permanent magnet synchronous machine (SMPMSM) by employing the computer framework consists of finite element analysis (FEA) and genetic algorithm (GA) utilized in the applications of electric vehicles. This framework aims to evaluate and determine the optimal setting of SMPMSMs, which require maximum average electromagnetic torque (Tem_avg) and minimum its ripple (Tem_rip). Several motor performances, such as magnetic field distribution across the motor, magnetic flux density distribution in the mid air gap, phase back-EMF, electromagnetic torque, and its ripple, are investigated for the initial and optimal designs of PM machines during open-circuit and on-load conditions by using FEA. The important parameter of PM machines, i.e. the magnet pole-arc and slot opening angle are taken into account. In order to determine the objective function of the GA framework, the Tem_avg and the Tem_rip are used to formulate the computing equations where the fitness value provided by the computing framework is further assessed. The GA framework is used to assess the comparison of parameters and motor performance between the initial and optimal designs of 12s/8p PM motors in terms of electromagnetic torque under BLAC operation. Consequently, the framework of FEA and GA has been proven in the design of SMPMSM, which is very viable for electric cars by reducing the magnet materials and electromagnetic torque ripple. -
PublicationOptimal Design of SMPMSM Using Genetic Algorithm Based on Finite Element Model( 2022-01-01)
;Mohd-Shafri S.A. ;Ishak D. ;Tan C.J. ;Leong J.H.This paper deals with an optimal design of a surface-mounted permanent magnet synchronous machine (SMPMSM) using a genetic algorithm (GA) method. To analyze the characteristic of permanent magnet (PM) motors, the classical optimization method, such as the finite element method (FEM), is intensively used. In this design, a three-phase 12-slot/8-pole PM motor is established with FEM with radial magnetization pattern. Then, the GA is used to search the optimality of SMPMSM machine design. In the final analysis, the optimal new design of SMPMSM is demonstrated by comparing it with the initial design that is investigated by FEM. The result of induced back-EMF, total harmonic distortion, and magnetic flux density of optimal design are compared with the initial design to show the advantages of GA optimization method. -
PublicationThe Influenced of Different Magnetization Patterns on the Performance of the Semi-buried Permanent Magnet Synchronous Machine( 2021-06-11)
;Syauqina Akmar Mohd-Shafri ;Muhamad Haniff Sani ;Ishak D. ;Tan C.J.The performance of semi-buried permanent magnet synchronous machines (SBPMSMs) by the influence of two magnetization patterns are presented in this paper. These magnetization patterns include radial and parallel, which applied into 9-slot/8-pole (9s/8p) and 6-slot/4-pole (6s/4p) SBPMSMs. Hence, to evaluate the machines performance, AutoCAD and Opera2D finite element software are used to model and predict the electromagnetic characteristic performance of SBPMSMs. Two PM machines are optimized i.e. flux density distribution, phase back-EMF, and cogging torque by two magnetization patterns. The phase back-EMF of the machines are computed into harmonic components to investigate the total harmonic distortion (THDv ). It is found that the lowest THDv for both 9s/8p and 6s/4p motors are in parallel magnetization (PaM), which are 8.66% and 3.98%, respectively. However, the lowest cogging torque for 9s/8p is radial magnetization (RaM), which is 0.0101 Nm and for 6s/4p is 0.1730 Nm with parallel magnetization pattern. By comparing the result of the optimum magnet pole arc for both motors, the 6s/4p motors show the minimum cogging torque and harmonic distortions are 0.16 Nm and 1.63% in PaM patterns. As a result, optimum motor performances among these two motors are 6s/4p PM motors with PaM pattern.2 -
PublicationDesign and Optimization of Electromagnetic Torque for a Surface-Mounted PMSM by using Subdomain Model and GA in Electric Vehicle Application( 2021-01-01)
;Syauqina Akmar Mohd Shafri ;Tan C.J. ;Ishak D.This paper presents a highly structured optimization strategy for 12-slot/8-pole surface-mounted permanent magnet synchronous machines (SMPMSM) with radial magnetization pattern. The main goals of the optimization process are to determine the optimal motor geometry, and achieving the minimum torque ripple and maximum average electromagnetic torque, simultaneously. The first function is used to obtain the maximum electromagnetic torque, and thus obtaining higher efficiency and the second function is used to achieve the minimum torque ripple. A computing framework that ensemble the genetic algorithm (GA) and subdomain model (SDM) with weighted equations is proposed to determine the optimal design of SMPMSM. After the optimization process, the optimal design of PM motor demonstrates much lower torque ripple with reasonable electromagnetic torque as compared with that of the initial design. The comparison of parameters and motor performances between the initial and the optimal designs of 12-slot/8-pole PM motors with the computing framework are validated in terms of electromagnetic torque under BLAC operation using SDM. Thus, the framework of SDM and GA is verified in reducing the usage of magnet materials and the electromagnetic torque ripple of SMPMSM, which is highly viable for electric vehicle. Therefore, the proposed ensemble framework of GA and SDM can determine the optimal settings of geometry design for SMPMSM in order to produce optimum motor performance.1 -
PublicationOptimal Design of SMPMSM Using SD-model based on Genetic Algorithm( 2021-01-01)
;Syauqina Akmar Mohd-Shafri ;Tan C.J. ;Ishak D.This paper deals with an optimal design of a surface-mounted permanent magnet synchronous machine (SMPMSM) with an exact analytical subdomain model by using a genetic algorithm method. To analyze the characteristic of permanent magnet (PM) motors, the classical optimization method, such as the finite element method (FEM), is intensively used. However, FEM has several time problems that require a longer computational time to evaluate the performance of PM motors. This problem can be overcome by using a genetic algorithm (GA) method combined with a subdomain model (SD), which developed an improved performance of SMPMSM, for instance, total harmonic distortion (THDv) and cogging torque. In this design, a three-phase 12-slot/8-pole PM motor is established with an exact SD model with RM and PaM magnetization patterns. Then, the GA ensemble with SD model to search the optimality of SMPMSM machine design. In the final analysis, the optimal new design of SMPMSM demonstrated by comparing with the initial design that is investigated by FEM. The result of induced back-EMF, cogging torque, total harmonic distortion, and magnetic flux density of optimal design is compared with the initial design to show the advantages of GA optimization method.1 -
PublicationOptimization Design of the Electromagnetic Torque for Surface-Mounted PMSM using GA and Finite Element Analysis for Electric Vehicle( 2021-01-01)
;Edric Wong Wee Ming ;Tan C.J. ;Syauqina Akmar Mohd-Shafri ;Ishak D.This paper presents an optimization design for a three-phase 12 mathrm{s}/8 mathrm{p} surface-mounted permanent magnet synchronous machine (SMPMSM) with a RM pattern applied in the electric vehicle by using the computing framework of finite element analysis (FEA) and genetic algorithm (GA). The framework is to determine the optimal settings of permanent magnet (PM) motor for higher average electromagnetic torque (T_{em_{-}avg}) and lower its ripple (T_{em_{-}rip}). Several motor performances are investigated for the initial and the optimal designs of PM machines during open-circuit and on-load conditions, i.e., magnetic field distribution across the motor, magnetic flux density distribution in the mid air gap, phase back-EMF, electromagnetic torque, and its ripple through FEA. The magnet pole-arc and slot opening angle of the PM motor are taken into consideration. The T_{em_{-}avg} and the T_{em_{-}rip} are employed to formulate the computing equations to determine the objective function, which is used to search the optimal settings of PM motor in GA framework, where the fitness value produced by the computing framework is further evaluated. The comparison of parameters and motor performances between the initial and the optimal designs of 12s/8p PM motors with the GA framework are validated in terms of electromagnetic torque under BLAC operation using FEA. Therefore, the framework of FEA and GA is verified in reducing the usage of magnet materials and the electromagnetic torque ripple in the design of SMPMSM, which is highly viable for electric vehicle.1