Modeling and Performance Analysis of Plug-In Split Hybrid Electric Vehicle

Regarding increasing of concern over the environment and ever stringent emissions regulations, the electric vehicle has been investigated as an alternative form of transportation. However, the electric vehicle suffers from relatively short range and long charging times and consequently has not become an acceptable solution to the automotive consumer. The addition of an internal combustion engine to extend the range of the electric vehicle is one method of exploiting the high efficiency and lack of emissions of the electric vehicle while retaining the range and convenient refuelling times of a conventional gasoline powered vehicle. The term that describes this type of vehicle is a hybrid electric vehicle. Many configurations of hybrid electric vehicles have been designed and implemented, namely the series, parallel and power-split configurations. This project discusses the modelling and simulation of split plug-in hybrid electric vehicles. Modelling methods such as physics-based Resistive Companion Form technique and Bond Graph method are presented with powertrain component and system modelling examples. The modelling and simulation capability of existing tools such as ADvanced VehIcle SimulatOR (ADVISOR) is demonstrated through application examples. Since power electronics is indispensable in hybrid vehicles, the issue of numerical oscillations in dynamic simulations involving power electronics is briefly addressed

Type 2 electric vehicle charger compatible for single phase and three phase

Design and development of a type 2 Electric Vehicle charger that is compatible for single phase and 3 phase that is cost effective. The Electric Vehicle charger are able to charge electric vehicle in both single phase and three phase. The Electric Vehicle charger are able to stop the charging automatically once the electric vehicle and been fully charged. The cost of the Electric Vehicle charger is low as compared to other commercial electric vehicle charger in the market. The Electric Vehicle charger is compliance to IEC62196

An application of teaching–learning-based optimization for solving the optimal power flow problem with stochastic wind and solar power generators

This paper proposes the implementation of metaheuristic algorithm namely, teaching–learning-based optimization (TLBO) algorithm to solve optimal power flow (OPF) problem. TLBO is inspired by philosophy of teaching and learning in the classroom. OPF on the other hand, is one of the most complex problems in power system operation, where in this paper, two objective functions aimed to be minimized by TLBO namely cost minimization and combined cost and emission (CEE) minimization. The effectiveness of proposed TLBO in solving the OPF is tested on modified IEEE-57 bus system that integrated with stochastic wind and solar power generations. To show the effectiveness of the proposed TLBO, several recent algorithms that have been proposed in literature will be utilized and compared. The simulations demonstrate the superiority of TLBO as an effective alternative solution for the OPF problems, where for the cost minimization, TLBO able to obtained 0.16% cost saving per hour compared to the second best algorithm; and for the CEE minimization, TLBO outperformed the second best algorithm by 0.12% cost saving per hour

Development of High Power LED Driver Using LTSpice Software

LED technology has been used widely in various applications due to its advantage in term of functionality, high efficiency, low cost, small size and high reliability. In order to improve LED performance and prolong LED’s life, High Power LED driver is been developed. LED driver is used to control output voltage by using current mode controlled method. This development of LED driver can increase the LED operation efficiency, provide high voltage protection, decreases the driver size and lastly make possible of user friendly installation. Voltage source is step up by using boost converter as main circuit. In control circuit, current mode controlled is used to regulate output characteristic of High Power LED. LTC 3783 is used as PWM controller to drive the gate and provide pulse signal to the MOSFET. This driver is designed to operate load that consists of 6 units LED each rating of 5 Watt connected in series. Theoretical calculation is made to obtain component specification. The LTspice software is used to simulate the driver circuit by using calculated parameters before move on to hardware implementation. Eagle software is used to design the Printed Circuit Board (PCB). Then, all components are mounted on the PCB which is made of FR4 material. The hardware built is tested experimentally and the output waveform is recorded

Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane

This paper presents the identification of double pendulum overhead crane (DPOC) plant based on the hybrid Multi-Verse Optimizer with Sine Cosine Algorithm (HMVOSCA) using the continuous-time Hammerstein model. In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). Moreover, an average position is chosen by computing the mean between the current position and the current best position obtained so far. These modifications are mainly for balancing exploration and exploitation and escaping from local optima and expected better identification accuracy of the DPOC plant. In the Hammerstein model identification, a continuous-time linear subsystem is used, which is more suitable for representing any real plant. The HMVOSCA algorithm is used to tune the linear and nonlinear parameters to reduce the gap between the estimated results and the actual results. The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. The experimental findings illustrate that the HMVOSCA algorithm can identify a Hammerstein model that generates an estimated output like the actual DPOC system output. Moreover, the identified results also show that the HMVOSCA algorithm outperforms other existing metaheuristics algorithms

Modified multi verse optimizer for solving optimization problems using benchmark functions

The hybrid version of multi-verse optimizer (MVO) namely the modified multi-verse optimizer (mMVO) is developed in this paper by modifying the position updating equation of MVO. Here two modification is proposed in the standard MVO. Firstly, an average position selection mechanism is proposed for solving the local optima problem and secondly, the MVO algorithm is hybrid with another metaheuristics algorithm namely the Sine Cosine Algorithm (SCA) for better balancing the exploration and exploitation of standard MVO algorithm so that it can improve its searching capability. The proposed version of MVO has been evaluated on 23 well known benchmark functions namely unimodal, multimodal and fixed-dimension multimodal benchmark functions and the results are then verified with the standard MVO algorithm. Experimental results demonstrate that the proposed mMVO algorithm gives much better improvement than the standard MVO in the optimization problems in the sense of preventing local optima and increasing the search capability

Metaheuristics algorithms to identify nonlinear Hammerstein model: A decade survey

Metaheuristics have been acknowledged as an effective solution for many difficult issues related to optimization. The metaheuristics, especially swarm’s intelligence and evolutionary computing algorithms, have gained popularity within a short time over the past two decades. Various metaheuristics algorithms are being introduced on an annual basis and applications that are more new are gradually being discovered. This paper presents a survey for the years 2011-2021 on multiple metaheuristics algorithms, particularly swarm and evolutionary algorithms, to identify a nonlinear block-oriented model called the Hammerstein model, mainly because such model has garnered much interest amidst researchers to identify nonlinear systems. Besides introducing a complete survey on the various population-based algorithms to identify the Hammerstein model, this paper also investigated some empirically verified actual process plants results. As such, this article serves as a guideline on the fundamentals of identifying nonlinear block-oriented models for new practitioners, apart from presenting a comprehensive summary of cutting-edge trends within the context of this topic area

Experiment on Power Quality of PV-grid System at FKEE UMP

This paper presents experiments of PV-grid system operation for a day light consisting of Photovoltaic (PV) – Inverter system as the renewable source connected to a network of induction motor as the load. A small-scale laboratory consists of Photovoltaic, Inverter, and loads system was setup. One power supplies from PV and grid were connected to single phase induction motors. In the experiment, both energy supplies from the grid and photovoltaic system were connected to the loads. Measurements have been done at both side of power transformer to analyze power quality in the system

Photovoltaic power system simulation for small industry area

In this paper, modeling and simulation of 1MW grid connected PV system is simulated using National Renewable Energy Laboratory's (NREL) HOMER software, and the optimum system is analyzed to see the economic feasibility of the system in a small industry area in Malacca, Malaysia. The system is expected to foresee reduced grid energy consumption. Emphasis is also placed on reduction of green house gases emission. HOMER will simulate the system and perform optimization of system according to the available usage data and the available renewable energy (sun radiation) data. The lifecycle and cost of each system modules will also affect the optimization duly. In addition, HOMER also performs optimizations according to different assumption of uncertain factors to gauge the effect of sensitivity list

Efficiency analysis of PV inverter – adjustable speed drive system

This project entails efficiency analysis of a distributed generation system consisting of Photovoltaic (PV) – Inverter system as the renewable source connected to a network of Adjustable Speed Drives (ASDSs) as the load. A small-scale laboratory of the Photovoltaic, Inverter, ASDSs and Loads system were used in this research. Two power supplies from PV and grid were connected to three ASDSs which powered three separate induction motors. Experiments were carried out. Measurements were recorded from which the interaction between the source and the load in this system may further be analyzed. Analysis of the result was carried out in which results of both experiments were compared. At the end of the research project, the worst and best case operating scenarios were indentified from which base-line information for optimum operating conditions is achieved