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About this book

This book presents recent developments in the areas of engineering and technology, focusing on experimental, numerical, and theoretical approaches. In the first part, the emphasis is on the emerging area of electromobility and its sub-disciplines, e.g. battery development, improved efficiency due to new designs and materials, and intelligent control approaches. In turn, the book’s second part addresses the broader topic of energy conversion and generation based on classical (petrol engines) and more modern approaches (e.g. turbines). The third and last part addresses quality control and boosting engineering efficiency in a broader sense. Topics covered include e.g. modern contactless screening methods and related image processing.

Table of Contents

Frontmatter

Study the Effect of Acetone as an Inhibitor for the Performance of Aluminium-Air Batteries

Abstract
Aluminium-air battery have high energy density, for example 8100 Wh kg−1 capable of replacing classical lithium based batteries. However, the presence of parasitic reactions during the discharge process causes reducing the lifetime of the aluminium-air battery. Organic inhibitors are able to prevent the parasitic reaction, but it is likely to effect the battery performance. The aim of this research is to study the effect of acetone as an inhibitor at aluminium-air battery. Density functional theory (DFT) with B3LYP functional and 6-311G(d,p) basis set was conducted to determine the inhibitor efficiency of acetone. Besides, the aluminium-air battery was developed and tested to identify battery performances by applying acetone with different concentrations (0, 2, 4, 6, and 8 mM). Results show that increasing the acetone concentration will improve the inhibitor’s efficiency from 12.5 to 50.0%. Further, the capacity of the battery can be increased with the inhibitor concentration. It is observed that the battery capacity using acetone (8 mM) is 0.028 Ah better than for a battery without acetone, 0.023 Ah. Therefore, acetone can be considered as an inhibitor capable of preventing severe corrosion against aluminium alloys and produces a good performance of aluminium-air batteries.
Mohamad-Syafiq Mohd-Kamal, Muhamad Husaini Abu Bakar, Sazali Yaacob

Performance Characteristics of Palm Oil Diesel Blends in a Diesel Engine

Abstract
Continuous usage and excavation of crude petroleum create a global alarm that in several years, the petroleum resources would be depleted. Researches on biomass resources such as palm oil, to replace diesel fuel have been conducted comprehensively to find the most suitable alternative fuel to diesel fuel. Blends of 20, 40, 60, 80 and 100% of palm oil (PO) with diesel were investigated in a single cylinder diesel engine. Each blend was tested on a standard Yanmar 178F diesel engine at various engine speeds (1000–1800 rpm) and various loads (200–1000 kW). The performance and fuel consumption of the engine were analysed and compared. Experimental results show that performance and fuel consumptions of the engine may produce better, equal or deteriorate when running on palm oil diesel blends.
Shahril Nizam Mohamed Soid, Mohamad Ariff Subri, Mohammad Izzuddin Ariffen, Intan Shafinaz Abd. Razak

Optimization of Palm Oil Diesel Blends Engine Performance Based on Injection Pressures and Timing

Abstract
The usage of palm oil diesel blends as an alternative fuel in a diesel engine has been proven by many researchers. However, the high viscosity of palm oil produced heavy low-volatility compounds that are difficult to combust in the main combustion phase, and produce longer combustion period when compared to diesel. This phenomenon will contribute to poor engine performance. Therefore, this research was conducted to optimize the engine performance based on different injection pressures and timings. Blends of 20 to 100% of palm oil (PO) and diesel were investigated on a standard Yanmar 178F diesel engine at various engine speeds, loads, injection pressures and timings. The optimization was carried out by using a design of experiment software. Experimental results show that the blends can match the diesel engine performance at higher injection pressure.
Shahril Nizam Mohamed Soid, Mohamad Ariff Subri, Muhammad-Najib Abdul-Hamid, Mohd Riduan Ibrahim, Muhammad Iqbal Ahmad

The Potential of Improving the Mg-Alloy Surface Quality Using Powder Mixed EDM

Abstract
The conventional electro-discharge machining (C-EDM) method with low material removal rate (MRR) and high electrode wear rate (EWR) results in high production costs. The C-EDM also suffers from inconsistent machined surface quality and the formation of micro cracks and craters on the machined surface. The objective of this article is to review the advantages of the powder mixed EDM (PMEDM) method and its potential to improve the Mg-alloy surface quality. Research articles related to PMEDM process since the year 2015 until 2018 are summarized in this article. The addition of conductive particles in the dielectric fluid leads to an increase of the spark gap size, which subsequently results in a reduction in electrical discharge power density. The melted and deposited zinc particles on the Mg-alloy machined surface will modify the surface.
M. A. Razak, A. M. Abdul-Rani, A. A. Aliyu, Muhamad Husaini Abu Bakar, M. R. Ibrahim, J. A. Shukor, A. Abdullah, M. Rezal, M. F. Haniff, F. Saad

Validation of Driver’s Cognitive Load on Driving Performance Using Spectral Estimation Based on EEG Frequency Spectrum

Abstract
Driver’s drowsiness becomes a prominent factor that causes the growing number of a road accident in the past few years and turns out to be perturbing for road safety. This research presents approaches for drowsiness and alertness recognition based on the electroencephalography (EEG) and power spectrum to evaluate the driver’s vigilance level in a static driving simulator. The EEG databases are validated using the Karolinska sleepiness scale (KSS) and reaction time (RT). Frequency-domain power spectral density (PSD) feature extraction techniques were evaluated (periodogram, Lomb-Scargle, Thompson multitaper, and Welch) with supervised learning classifiers (MLNN, QSVM, and KNN). The highest accuracy is attained from MLNN using Lomb-Scargle PSD with 96.3% and the minimum accuracy is attained from QSVM and KNN with both 62.2% using periodogram and Welch PSD features set respectively.
Firdaus Mohamed, Pranesh Krishnan, Sazali Yaacob

Analytical Study of a Cylindrical Linear Electromagnetic Pulsing Motor for Electric Vehicles

Abstract
The cylindrical linear electromagnetic pulsing motor (EMPM) is an alternative electric vehicle (EV) to be simulated in this study. The proposed design on the cylindrical linear EMPM will replace the piston engine in an internal combustion engine (ICE) which produces linear motion. It can eliminate problems related to internal combustion engines (ICE) such as engine weight and friction where fewer components have been used. In this paper, an analytical model was constructed and predicted the magnetic equivalent circuit (MEC) that can solve with the same technique as the electrical circuit. The initial magneto-statics analysis was conducted through the finite element magnetic software (FEMs) for magnetic filed problem so that the magnetic flux relationship could be predicted. Furthermore, the FE modelling and analysis is followed by a MATLAB/Simulink software calculation to predict the cylinder linear EMPM. Finally, the simulation results of the FE models regarding plunger force, thrust, plunger distance, speed, and power motor were presented and compared with the regulated counterparts obtained from the experimental setup.
N. M. Noor, Ishak Aris, S. Arof, A. K. Ismail, K. A. Shamsudin, M. Norhisam

Investigation on Effective Pre-determined Time Study Analysis in Determining the Production Capacity

Abstract
In this paper, the application of pre-determined time study analysis in determination of production capacity had been investigated to understand the accuracy level of production capacity. In determination of production capacity, normally motion time study analysis is conducted for actual production processes to define the bottleneck process and production capacity. However, for new product introduction (NPI), the calculation of the labor cost and the unfamiliar production process is normally based on assumptions or benchmarking from similar processes. As introduced by Maynard Operation Sequence Technique (MOST®), it helps the industries in determining the production capacity. The dilemma of industries is the level of accuracy for a pre-determined time study at the beginning stage of production. This research has been conducted by examining the accuracy of pre-determined time study using the MOST® technique in selected case study industries and the results of this study show that the level of accuracy achieved is at 83.84%.
Mohd Norzaimi Che Ani, Ishak Abdul Azid

Vibration Measurement on the Electric Grass Trimmer Handle

Abstract
It is important to reduce the vibration level on the electric grass trimmer so that it is safe to be used by the user to avoid illness such as white fingers. The objective of this study is to measure the vibration level of an existing electric grass trimmer and to reduce the vibration level at the handle of the electric grass trimmer. The vibration level has been measured by two types of experiments which are spectral testing and impact test for modal analysis. A new handle has been designed by adding a spring stiffness in order to reduce the vibration level. Vibration level of the new handle is 0.22 g. After that, an active vibration control system (AVC) is developed using the LabVIEW system which applied a block diagram as its interface and solenoid as its actuator.
Muhammad-Najib Abdul-Hamid, Farahiyah Mahzan, Shahril Nizam Mohamed Soid, Zainal Nazri Mohd Yusuf, Nurashikin Sawal

Low Harmonics Plug-in Home Charging Electric Vehicle Battery Charger Utilizing Multi-level Rectifier, Zero Crossing and Buck Chopper

Part 1: General Overview
Abstract
This paper focuses on developing a battery charger for electric car. A novel topology of a battery charger is proposed. Conventional rectifier has drawbacks in term of harmonic currents. This paper describes about a five level single-phase rectifier associated with zero crossings circuit and buck chopper with a control signal which draws a clean sinusoidal line current for the application of low harmonics plug in home charging Electric Vehicle battery charger. The MATLAB/Simulink results reveal the proposed Electric Vehicle battery charger performance compared to the conventional method.
Saharul Arof, N. H. N. Diyanah, Philip Mawby, H. Arof, Nurazlin Mohd Yaakop

A New Four Quadrants Drive Chopper for Separately Excited DC Motor in Low Cost Electric Vehicle

Abstract
Four quadrants DC chopper systems are widely used in dc drive traction for electric vehicles. However, detail information on the design and method of operation for the systems were rarely addressed in the research literature. Accordingly, this study aimed to contribute on a new topology of a Four Quadrants Drive DC Chopper for separately excited dc motor. The chopper is designed to operate in five operation modes; driving, field weakening, generation, regenerative braking and resistive braking for the application of a low cost Electric Vehicle. The chopper modes of operation are further described and simulated using MATLAB/SIMULINK. Results on chopper performance, i.e. switching power losses, ripple torque and current, voltage drop and output power, regenerative braking power and control were discussed. The proposed chopper operations have been verified through experimental setup and the chopper is observed to be capable of performing the expected operations.
S. Arof, N. H. N. Diyanah, N. M. Noor, J. A. Jalil, P. A. Mawby, H. Arof

Genetics Algorithm for Setting Up Look Up Table in Parallel Mode of Series Motor Four Quadrants Drive DC Chopper

Abstract
This paper presents the establishment of look-up table (LUT) for speed versus field current. LUT is necessary as an input reference for the close loop control of field current. The LUT was developed with the assistance of a genetic algorithm (GA). GA was used for optimization of the field current to maintain the motor torque for DC series motor running in parallel mode. Other than that, the LUT was employed when the FQDC was run in parallel mode for the purpose of climbing up a steep hill or slope. The simulation results using MATLAB/Simulink showed that the DC series motor with the assistance of LUT could overcome the drawbacks of DC series motor as speed decreases drastically when climbing a steep hill. In conclusion, the GA had successfully determined the best optimum field current to produce the highest torque to overcome load effect when tested using the proposed Four-Quadrant DC Chopper.
S. Arof, N. H. N. Diyanah, N. M. N. Noor, M. Rosyidi, M. S. Said, A. K. Muhd Khairulzaman, P. A. Mawby, H. Arof

Series Motor Four Quadrants Drive DC Chopper

Part 4: Generator Mode
Abstract
This paper is the part four (4) of the total 8 papers of the series motor four quadrants DC chopper that describes the generator mode operation of a four quadrant drive DC chopper that is applicable for EV traction. Alternative excitation methods proposed in this work resulted in greater build up voltage and armature current of the series motor when operating in generator mode. In order to achieve a longer traversed distance, the converter of an EV should utilize the optimum amount of power from the batteries at all time. Hence, the work has been extended to a simulation of the battery charging process and the effect due to huge voltage difference between the generated voltage and battery terminal voltage. The operation mode is modelled and simulated in MATLAB/SIMULINK and the proposed excitation methods have been verified through experimental set-up.
S. Arof, N. H. N. Diyanah, N. M. N. Noor, Md. Radzi, J. A. Jalil, P. A. Mawby, H. Arof

Relationship Between Electrical Conductivity and Total Dissolved Solids as Water Quality Parameter in Teluk Lipat by Using Regression Analysis

Abstract
This study investigated the relationship between electrical conductivity and total dissolved solids (TDS) as water quality parameters at Teluk Lipat coastal area. Teluk Lipat is located at the East coast of Malaysia peninsula that is directly exposed to the South China Sea. 13 water samples from this area were collected to determine of electrical conductivity (EC) and total dissolved solids (TDS). From the regression analysis between electrical conductivity (EC) and total dissolved solids (TDS), it shows a very strong relationship between these two parameters with R2 value of 0.9306 but it was still not a perfect straight line. This analysis can be used to give an over-view of water quality.
Nor Haniza Bakhtiar Jemily, Fathinul Najib Ahmad Sa’ad, Abd Rahman Mat Amin, Muhammad Firdaus Othman, M. Z. Mohd Yusoff

A Study of the Region Covariance Descriptor: Impact of Feature Selection and Precise Localization of Target

Abstract
In visual tracking, selecting the right image descriptors is critical. The popular version of descriptor is known as the covariance descriptor; however, no further studies is yet developed regarding the different methodologies for its construction. This study analyzes the contribution of diverse features of an image to the descriptor and their contribution to the detection of arbitrary targets in sequences of images, in our case: Boy, David3, Bolt and Walking2 in an image sequence. The methodology to determine the performance of the covariance matrix is defined from different sets of characteristics, and a specific combination of features is needed to develop a correlation between them. Finally, when an analysis is performed with the best set of features, F4 the target detection problem reached a performance of average, 0.77, From this experiment, it is believed that we have constructed a greater solution in choosing best features for this descriptor, allowing to move forward to the next issues such as using it on others datasets.
Mohd Fauzi Abu Hassan, Azurahisham Sah Pri, Zakiah Ahmad, Tengku Mohd Azahar Tuan Dir

Analysis of a Micro Francis Turbine Blade

Abstract
The main purpose of the turbine is to extract energy into the useful work. The high pressure of the water from the head will be applied to the blade. Long term exposure of this high pressure will lead to the blade metal become fatigue and cause a fracture. The objectives of this study are to obtain the total deformation and stresses that act on the blade. There are few new designs of the blade from to previous studies will be consider. The turbine blade is simulated using the finite element method (FEM) based on the commercial code ANSYS. The result of the datum design is compared with all new designs in order to analyze if the new design is better or vice versa from the datum design. The best design is selected based on the largest percentages difference of the selected design compared to the datum design. Using statistical analysis, paired comparison design is selected to compare between the datum design and the selected design, i.e. do the results have a significant difference. It can be concluded that the new design is better in handling the total deformation, stress and strain.
K. Shahril, A. Tajul, M. S. M. Sidik, K. A. Shamsuddin, A. R. Ab-Kadir

Deep Contractive Autoencoder-Based Anomaly Detection for In-Vehicle Controller Area Network (CAN)

Abstract
With the emerging wireless technology integrated into modern vehicles, this introduces an enormous number of vulnerabilities for adversaries to compromise the vehicle internal system. Nonetheless, the attacks can be alleviated using anomaly detection mechanism which have been proven to be effective in monitoring and detecting attacks. In this paper, we developed an anomaly detection using an unsupervised deep learning-based approach, known as Deep Contractive Autoencoders (DCAEs). The DCAEs, which is one of the regularize autoencoders model imposed a different penalty term to the CAN data representation in order to encourage robustness towards small changes. To accomplish this purpose, we captured CAN bus data from three different vehicles, pre-processed them using the max absolute normalization, and evaluated the model over three types of attacks. Finally, the experimental results demonstrated that DCAEs yield a 91–100% detection rate which outperformed other variants of regularized autoencoders.
Siti Farhana Lokman, Abu Talib Othman, Shahrulniza Musa, Muhamad Husaini Abu Bakar

Design and Temperature Analysis of an Aluminum-Air Battery Casing for Electric Vehicles

Abstract
The aluminum-air battery receives more attention to applications in electronic mobile devices, transportation systems, and has a higher energy density than other metal-air batteries. However, the aluminum-air battery is still not widely commercialized due to unacceptably thermal issues. Hence, this study focuses on the development of an aluminum-air battery casing, studies the performance of the aluminum-air battery and thermal distribution analysis by using thermography. A single cell with dimensions of 10 cm × 10 cm × 3 cm with an anode area of 6.5 cm2 and an air cathode area of 6.5 cm2 is designed. In addition, 1 M of NaOH acts as the electrolyte of the battery. The aluminum-air battery temperature distribution is determined by a thermal imaging camera. The maximum temperature of 34 °C has been found as the reaction occurs. The result of the battery tests shows that the battery can produce a maximum voltage of 1.5 V and has a constant current value of 40 mA. The discharge rate of the battery indicates that one cell can operate for 10 h. Thus, the proposed design for the battery casing has functioned at the optimal condition.
Mohamad Naufal Mohamad Zaini, Mohamad-Syafiq Mohd-Kamal, Mohamad Sabri Mohamad Sidik, Muhamad Husaini Abu Bakar

Corrosion Analysis of Aluminum-Air Battery Electrode Using Smoothed Particle Hydrodynamics

Abstract
Aluminum-air (Al-air) battery becomes one of the demanding batteries to power up an electronic device in our daily life. However, the corrosion behaviour of aluminium anodes is a major issue that must be carefully considered in the Al-air battery. This study is aimed to develop an Al-air battery single cell model and to simulate the corrosion by using the Smoothed Particle Hydrodynamics (SPH) method. The rate of corrosion at the anode and the effect of this corrosion to the performance of the Al-air battery is being study. As a result, the velocity profile of the anode corrosion and the electrolyte flow has been determined. These two measured parameters are closely significant toward corrosion behaviour. Thus, it has been proven that the SPH method is capable of modelling and simulating the corrosion behaviour in Al-air batteries.
Faizah Osman, Amir Hafiz Mohd Nazri, Mohamad Sabri Mohamad Sidik, Muhamad Husaini Abu Bakar

Development of an Aluminum-Air Battery Using T6-6061 Anode as Electric Vehicle Power Source

Abstract
The demand for a long-lasting batteries for electric vehicle has increased throughout the years. The common rechargeable lithium-ion battery cannot fulfill this task. The Aluminum-air battery is an attractive candidate as it has a high power density. However, it has a high rate of corrosion on the anode electrode due to the aluminum reaction with the electrolyte. It becomes a challenge for researchers to make an ideal aluminum-air battery. The aim of this research is to determine the appropriate anode material’s (pure aluminum or 6061-T6) for aluminum-air batteries. Two experiments, i.e. measuring the volume of hydrogen gas released and weight loss measurements of the aluminum metal before and after reaction with the electrolyte NaOH were performed using a specific experimental setup. The corrosion rate and the hydrogen gas evolution rate were calculated. Experiments were carried out with a molarity of 2, 3 and 4 M of NaOH with 10 min of immersion. The mass of specimens was measured by using an electronic digital weighing scale. As a result, it is found that the alloy elements enhance the corrosion resistivity of metal (aluminum).
Faizah Osman, Mohd Zulfadzli Harith, Mohamad Sabri Mohamad Sidik, Muhamad Husaini Abu Bakar

Synthesis and Thermal Characterization of Graphite Polymer Composites for Aluminium Ion Batteries

Abstract
Phenolic resin is a thermosetting polymer resin is that is known for its excellent thermal properties and chemical stability. Thus, it could be advantageous if it could be utilized in graphite polymer composites as the cathode in aluminium ion batteries. In this study, graphite polymer composites with 3 cm of diameter and 3 cm of thickness had been fabricated and then their thermal characteristics were determined. The composition ratios of 40/60, 50/50, 60/40 and 70/30 by their weight percentage (wt%) of graphite/phenol respectively were fabricated using the hot compression method. Any further increment of graphite percentage in the composition would produce a very fragile composite. In the physical properties characterization, the bulk density, true density, and porosity percentage were determined. Besides, the thermal conductivity of the graphite composites had been measured according to ASTM E1350 standard for thermal characterization. It is observed that an increase in graphite content results in an increase in porosity content and thus reducing its thermal conductivity. It is concluded that a composition of 40/60 and 50/50 by its %wt of graphite/phenol has good physical and thermal properties with ~1.7 g/cm3, 6–8%, and ~36 W/mK of bulk density, porosity percentage and thermal conductivity, respectively.
Faizatul Azwa Zamri, Najmuddin Isa, Muhamad Husaini Abu Bakar, Mohd Nurhidayat Zahelem

Design and Analysis of an Aluminium Ion Battery for Electric Vehicles

Abstract
The Lithium-ion battery has been widely used in the development of electric vehicles. However, awareness of battery safety has been encouraged to use aluminium based batteries. Therefore, in this study, an aluminium ion battery cell with 25 mm × 100 mm of diameter and height respectively was designed using the SolidWorks 2016 software. Then the aluminium-ion battery was fabricated using different electrolyte types including potassium hydroxide (KOH), sodium hydroxide (NaOH) and a mixture of sodium hypochlorite with sodium hydroxide (NaOCl + NaOH) to determine the battery characteristics. The battery characteristics were obtained using an Arduino battery performance tester connected to the PLX-DAQ software as an interface. A thermography test was also performed to observe the heat distribution on the outer surface of the battery using a thermal imager model U5855A TruIR thermal imager connected to the TrueIR Analysis and Reporting Tool software. It is observed that aluminium-ion battery using a mixture of sodium hypochlorite with sodium hydroxide provides good battery characteristics which specific voltage and current density obtained as 1.13 V for and 79.31 mA respectively with 8 h operating time. The heat distribute over the surface was moderate with the highest temperature of 37 °C and constantly for 15 min. As a conclusion, an aluminium-ion battery has been developed for future review in electric vehicles application.
Faizatul Azwa Zamri, Mohamad Zhairul Faris Jumari, Muhamad Husaini Abu Bakar, Mohd Nurhidayat Zahelem

Automotive Metallic Component Inspection System Using Square Pulse Thermography

Abstract
This paper presents an alternative inspection system for automotive components replacing the conventional way by using naked human eye and ultrasonic which are normally quiet time consuming. In order to solve the time consumption issue, we propose the thermography technique which has the capability to detect the internal defect in an efficient way and is proven to be one of the active thermography types. The process involves: (i) developing the square pulse thermography inspection system for automotive components. The time duration of heating is 7 min 10 s with 3002 sequence of an image, (ii) analyzing the effect of defect magnitude on the surface temperature distribution, and finally, (iii) determining a defect profile in a metallic element. The diameter of the defect is evaluated by calculating the ratio between the physical size and the pixel number. As a result, the defect of 12 artificial holes can be detected with less than 10% error. As a consequence, the proposed thermography method has a good potential to be utilized in an automotive inspection system.
Nor Liyana Maskuri, Elvi Silver Beli, Ahmad Kamal Ismail, Muhamad Husaini Abu Bakar

Deep Neural Network Modeling for Metallic Component Defects Using the Finite Element Model

Abstract
Nowadays, quality assurance is important for companies that are manufacturing components for various uses especially in the automotive industries. However, the inspection systems for determining the quality of these components are usually done by human workers which sometimes lead to inconsistencies. In order to counter this issue, an image classification-based technique using a Convolutional Neural Network (CNN) algorithm is introduced in this paper. The CNN provides a better approach in learning a feature data hierarchy to distinguish among samples of the defect and non-defect data represented as colored images. The process involves: (i) Region extraction using the finite element model, (ii) Formulate the model using a deep learning-based CNN algorithm, (iii) Defect detection. Four sets of metal dataset were used to train the model and to verify the accuracy and stability of the proposed method. The results demonstrated that the proposed CNN model can predict defects and non-defects data with the accuracy of 100%, precision of 99%, recall of 100%, and F1-score of 100%. Based on the experimental result, the proposed model is expected to be promising due to its robustness which can be used to detect defects in an online detection in ensuring quality manufacturing components.
Liyana Isamail, Nor Liyana Maskuri, Neil Jeremy Isip, Siti Farhana Lokman, Muhamad Husaini Abu Bakar
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