scholarly journals Comparison of the Economic and Environmental Performance of V2H and Residential Stationary Battery: Development of a Multi-Objective Optimization Method for Homes of EV Owners

2019 ◽  
Vol 10 (4) ◽  
pp. 78
Author(s):  
Ryosuke Kataoka ◽  
Akira Shichi ◽  
Hiroyuki Yamada ◽  
Yumiko Iwafune ◽  
Kazuhiko Ogimoto
Keyword(s):  
Electric Vehicles ◽  
Environmental Performance ◽  
Optimization Method ◽  
Energy Costs ◽  
Multi Objective Optimization ◽  
Environmental Aspects ◽  
Multi Objective ◽  
Investment Cost ◽  
Detached House

The use of batteries of electric vehicles (EVs) for home electricity applications using a bidirectional charger, a process called vehicle-to-home (V2H), is attracting the attention of EV owners as a valuable additional benefit of EVs. To motivate owners to invest in V2H, a quantitative evaluation to compare the performance of EV batteries with that of residential stationary batteries (SBs) is required. In this study, we developed a multi-objective optimization method for the household of EV owners using energy costs including investment and CO2 emissions as indices and compared the performances of V2H and SB. As a case study, a typical detached house in Japan was assumed, and we evaluated the economic and environmental aspects of solar power self-consumption using V2H or SB. The results showed that non-commuting EV owners should invest in V2H if the investment cost of a bidirectional charger is one third of the current cost as compared with inexpensive SB, in 2030. In contrast, our results showed that there were no advantages for commuting EV owners. The results of this study contribute to the rational setting of investment costs to increase the use of V2H by EV owners.

scholarly journals Problems of a Utopia Point Setting in Transformation of Individual Objective Functions in Multi-Objective Optimization

2019 ◽  
Vol 27 (45) ◽  
pp. 64-71
Author(s):  
Pavel Važan ◽  
Zuzana Červeňanská ◽  
Janette Kotianová ◽  
Jiří Holík
Keyword(s):  
Production Control ◽  
A Priori ◽  
Optimization Method ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Weighted Sum Method ◽  
The Individual ◽  
Utopia Point

Abstract In an optimal processes control, where the considered goals are in general observed as concurrently conflicted, a multi-objective approach fits the best. Commonly used scalarization techniques in multi-objective optimization need a transformation of the individual single-objective functions involved into a scalar multi-criteria objective function. There are many parameters which can influence the optimization results solutions, including an unreachable utopia point value. In this study, the authors compare the multi-objective problem solutions found via two ways of the individual objectives transformation with the respect to setting the utopia point. The methods are used in the area of production control in a case study for a batch production system. To find the solutions, The Weighted Sum Method with a priori articulated preferences under specific constraints as the scalar multi-objective optimization method is applied in simulation optimization.

scholarly journals Parameter Matching Optimization of a Powertrain System of Hybrid Electric Vehicles Based on Multi-Objective Optimization

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 875 ◽  
Author(s):  
Xiaoling Fu ◽  
Qi Zhang ◽  
Jiyun Tang ◽  
Chao Wang
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Powertrain System ◽  
Parameter Matching ◽  
Hybrid Electric ◽  
Fuel Consumption And Emissions

Aiming at problems of large computational complexity and poor reliability, a parameter matching optimization method of a powertrain system of hybrid electric vehicles based on multi-objective optimization is proposed in this paper. First, according to the vehicle basic parameters and performance indicators, the parameter ranges of different components were analyzed and calculated; then, with the weight coefficient method, the multi-objective optimization (MOO) problem of fuel consumption and emissions was transformed into a single-objective optimization problem; finally, the co-simulation of AVL Cruise and Matlab/Simulink was achieved to evaluate the effects of parameter matching through the objective function. The research results show that the proposed parameter matching optimization method for hybrid electric vehicles based on multi-objective optimization can significantly reduce fuel consumption and emissions of a vehicle simultaneously and thus provides an optimized vehicle configuration for energy management strategy research. The method proposed in this paper has a high application value in the optimization design of electric vehicles.

scholarly journals Efficient multi-objective optimization methods for computationally intensive urban water resources models

2014 ◽  
Vol 17 (1) ◽  
pp. 36-55 ◽  
Author(s):  
Mohammad Mortazavi-Naeini ◽  
George Kuczera ◽  
Lijie Cui
Keyword(s):  
Ant Colony Optimization ◽  
Water Resource ◽  
Optimization Methods ◽  
Optimization Method ◽  
Ant Colony ◽  
Urban Water ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective

Multi-objective optimization methods require many thousands of objective function evaluations. For urban water resource problems such evaluations can be computationally very expensive. The question as to which optimization method is the best choice for a given function evaluations budget in urban water resource problems remains unexplored. The main objective of this paper is to address this question. The second objective is to develop a new optimization algorithm, efficient multi-objective ant colony optimization-I (EMOACO-I), which exploits the good performance of ant colony optimization enhanced using ideas borrowed from evolutionary optimization. Its performance was compared against three established methods (NSGA-II, SMPSO, εMOEA) using two case studies based on the urban water resource systems serving two major Australian cities. The case study problems involved two or three objectives and 10 or 13 decision variables affecting infrastructure investment and system operation. The results show that NSGA-II was the worst performing method. However, none of the remaining methods was unambiguously superior. For example, while EMOACO-I converged more rapidly, its diversity was comparable but not superior to the other methods. Greater differences in performance were found as the number of objectives and case study complexity increased. This suggests that pooling the results from a number of methods could help guard against the vagaries in performance of individual methods.

scholarly journals Multi-Objective Optimization of the Gate Driver Parameters in a SiC-Based DC-DC Converter for Electric Vehicles

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3720
Author(s):  
Milad Moradpour ◽  
Paolo Pirino ◽  
Michele Losito ◽  
Wulf-Toke Franke ◽  
Amit Kumar ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Electromagnetic Interference ◽  
Optimization Problem ◽  
Experimental Tests ◽  
Wide Band ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Gate Driver ◽  
Efficient Power

DC-DC converters are being used for power management and battery charging in electric vehicles (EVs). To further the role of EVs in the market, more efficient power electronic converters are needed. Wide band gap (WBG) devices such as silicon carbide (SiC) provide higher frequency and lower power loss, however, their high di/dt and dv/dt transients result in higher electromagnetic interference (EMI). On the other hand, some gate driver parameters such as gate resistor ( R G ) have a contradictory effect on efficiency ( η ) and EMI. The idea of this paper is to investigate the values of these parameters using a multi-objective optimization method to optimize η and EMI at the same time. To this aim, first, the effect of high and low side R G on η and EMI in the half-bridge configuration is studied. Then, the objective functions of the optimization problem are obtained using a numerical regression method on the basis of the experimental tests. Then, the values of the gate resistors are obtained by solving the multi-objective optimization problem. Finally, η and EMI of the converter in the optimum gate resistor design are compared to those in the conventional design to validate the effectiveness of the proposed design approach.

Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Initial Step ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Prospective Students ◽  
Multi Objective

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.

Sign in / Sign up

Export Citation Format

Share Document