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Reliability-based robust multi-obj ective optimization of a 5-DOF vehicle vibration model subjected to random road profiles

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Journal of Central South University 2017年第1期24卷 104-113页

作者： abolfazl khalkhali Morteza Sarmadi Sina Yousefi Automotive Simulation and Optimal Design Research Laboratory School of Automotive EngineeringIran University of Science&TechnologyTehran 16846-13114Iran

Ride and handling are two paramount factors in design and development of vehicle suspension systems. Conflicting trends in ride and handling characteristics propel engineers toward employing multi-objective optimization methods capable of providing the best trade-off designs compromising both criteria simultaneously. Although many studies have been performed on multi-objective optimization of vehicle suspension system, only a few of them have used probabilistic approaches considering effects of uncertainties in the design. However, it has been proved that optimum point obtained from deterministic optimization without taking into account the effects of uncertainties may lead to high-risk points instead of optimum ones. In this work, reliability-based robust multi-objective optimization of a 5 degree of freedom （5-DOF） vehicle suspension system is performed using method of non-dominated sorting genetic algorithm-II （NSGA-II） in conjunction with Monte Carlo simulation （MCS） to obtain best designs considering both comfort and handling. Road profile is modeled as a random function using power spectral density （PSD） which is in better accordance with reality. To accommodate the robust approach, the variance of all objective functions is also considered to be minimized. Also, to take into account the reliability criterion, a reliability-based constraint is considered in the optimization. A deterministic optimization has also been performed to compare the results with probabilistic study and some other deterministic studies in the literature. In addition, sensitivity analysis has been performed to reveal the effects of different design variables on objective functions. To introduce the best trade-off points from the obtained Pareto fronts, TOPSIS method has been employed. Results show that optimum design point obtained from probabilistic optimization in this work provides better performance while demonstrating very good reliability and robustness. However, other optimum poi

关键词： probabilistic optimization vehicle suspension deterministic optimization ride handling genetic algorithm

Optimal design of functionally graded Pm PV/CNT nanocomposite cylindrical tube for purpose of torque transmission

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Journal of Central South University 2016年第2期23卷 362-369页

作者： abolfazl khalkhali Sharif Khakshournia Parvaneh Saberi Automotive Simulation and Optimal Design Research Laboratory School of Automotive EngineeringIran University of Science & Technology

Carbon nanotube(CNT)/polymer nanocomposites have vast application in industry because of their light mass and high strength. In this work, a cylindrical tube which is made up of functionally graded(FG) PmP V/CNT nanocomposite, is optimally designed for the purpose of torque transmission. The main confining parameters of a rotating shaft in torque transmission process are mass of the shaft, critical speed of rotation and critical buckling torque. It is required to solve a multi-objective optimization problem(MOP) to consider these three targets simultaneously in the process of design. The three-objective optimization problem for this case is defined and solved using a hybrid method of FEM and modified non-dominated sorting genetic algorithm(NSGA-II), by coupling two softwares, MATLAB and ABAQUS. Optimization process provides a set of non-dominated optimal design vectors. Then, two methods, nearest to ideal point(NIP) and technique for ordering preferences by similarity to ideal solution(TOPSIS), are employed to choose trade-off optimum design vectors. Optimum parameters that are obtained from this work are compared with the results of previous studies for similar cylindrical tubes made from composite or a hybrid of aluminum and composite that more than 20% improvement is observed in all of the objective functions.

关键词： nanocomposite carbon nanotube (CNT) fimctionally graded materials (FGM) cylindrical tube finite element method(FEM) modified NSGA-II technique for ordering preferences by similarity to ideal solution (TOPSIS) nearest to ideal point (NIP)

Optimal design of automotive body B-pillar using simplified finite element model of body-in-prime combined with an optimization procedure

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Journal of Central South University 2022年第12期29卷 3939-3955页

作者： Mehri IZANLOO abolfazl khalkhali Automotive Simulation and Optimal Design Research Laboratory School of Automotive EngineeringIran University of Science and TechnologyTehran 13114-16846Iran

Optimization of an automotive body structure faces the difficulty of having too many design variables and a too large design search space. A simplified model of body-in-prime(BIP) can solve this difficulty by reducing the number of design variables. In this study, to achieve lighter weight and higher stiffness, the simplified model of BIP was developed and combined with an optimization procedure;consequently, optimal designs of automotive body B-pillar were produced. B-pillar was divided into four quarters and each quarter was modelled by one simplified beam. In the optimization procedure, depth, width, and thickness of the simplified beams were considered as the design ***, bending and torsional stiffness were also considered as objective functions. The optimization procedure is composed of six stages: designing the experiments, calculating grey relational grade, calculating signal-to noise ratio,finding an optimum design using Taguchi grey relational analysis, performing sensitivity analysis using analysis of variance(ANOVA) and performing non-dominated sorting and multi-criteria decision making. The results show that the width of lower B-pillar has the highest effect(about 55%) and the obtained optimum design point could reduce the weight of B-pillar by about 40% without reducing the BIP stiffness by more than 1.47%.

关键词： body-in-prime(BIP)model finite element model bending stiffness torsional stiffness B-pillar Taguchi method multi criterion decision-making(MCDM)method

Hybrid multi-objective optimization of microstructural and mechanical properties of B_4C/A356 composites fabricated by FSP using TOPSIS and modified NSGA-Ⅱ

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Transactions of Nonferrous Metals Society of China 2017年第11期27卷 2317-2333页

作者： Mostafa AKBARI Mohammad Hasan SHOJAEEFARD Parviz ASADI abolfazl khalkhali School of Automotive Engineering Iran University of Science and TechnologyTehranIran School of Mechanical Engineering Iran University of Science and TechnologyTehranIran Faculty of Engineering Imam Khomeini International UniversityQazvinIran

A356alloy was used as the base metal to produce boron carbide(B4C)/A356composites using friction stir processing(FSP).The microstructural and mechanical properties of B4C/A356composites were optimized using artificial neural network(ANN)and non-dominated sorting genetic algorithm-II(NSGA-II).Firstly,microstructural properties of the composites fabricated in different processing conditions were *** show that FSP parameters such as rotational speed,traverse speed and tool pin profile significantly affect the size of the primary silicon(Si)particles of the base metal,as well as the dispersion quality and volume fraction of reinforcing B4C particles in the composite *** rotational to traverse speeds ratio accompanied by threaded pin profile leads to better particles distribution,finer Si particles and smaller B4C ***,hardness and tensile tests were performed to study mechanical properties of the *** changes the fracture mechanism from brittle form in the as-received metal to very ductile form in the FSPed ***,a relation between the FSP parameters and microstructural and mechanical properties of the composites was established using ANN.A modified NSGA-II by incorporating diversity preserving mechanism called theεelimination algorithm was employed to obtain the Pareto-optimal set of FSP parameters.

关键词： friction stir processing B4C composite multi-objective optimization TOPSIS method

Optimal design and applicability of electric power steering system for automotive platform

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Journal of Central South University 2019年第4期26卷 839-851页

作者： abolfazl khalkhali Mohammad Hassan SHOJAEEFARD Masoud DAHMARDEH Hadi SOTOUDEH Automotive Simulation and Optimal Design Research Laboratory School of Automotive EngineeringIran University of Science and Technology

The ongoing need for better fuel economy and lower exhaust pollution of vehicles has increased the employment of electric power steering(EPS)in *** design of EPS for a product family reduces the development and fabrication costs *** this paper,the TOPSIS method along with the NSGA-Ⅱis employed to find an optimum family of EPS for an automotive platform.A multi-objective optimization problem is defined considering road feel,steering portability,RMS of Ackerman error,and product family penalty function(PFPF)as the conflicting objective *** results for the single objective optimization problems and the ones for the multi-objective optimization problem,as well as two suggested trade-off design points are presented,compared and *** the two suggested points,performance at one objective function is deteriorated by about 1%,while the commonality is increased by 20%–40%,which shows the effectiveness of the proposed method in first finding the non-dominated design points and then selecting the trade-off among the obtained *** results indicate that the obtained trade-off points have superior performance within the product family with maximum number of common parts.

关键词： product family optimization optimal platform design NSGA-Ⅱ TOPSIS electric power steering