Multi-objective optimization of quarter car passive suspension design in the frequency domain based on PSO

2016 ◽  
Vol 33 (5) ◽  
pp. 1422-1434 ◽  
Author(s):  
Herbert Martins Gomes
Keyword(s):  
Frequency Domain ◽  
Optimization Design ◽  
Heuristic Algorithms ◽  
Computational Effort ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Passive Suspension ◽  
Multi Objective ◽  
Suspension Parameters ◽  
Quarter Car

Purpose – The purpose of this paper is to investigate the optimum design of a quarter car passive suspension system using a particle swarm optimization algorithm in order to minimize the applied loads and vibrations. Design/methodology/approach – The road excitation is assumed as zero-mean random field and modeled by single-sided power spectral density (PSD) based on international standard ISO 8608. The variance of sprung mass displacements and variance of dynamic applied load are evaluated by PSD functions and used as cost function for the optimization. Findings – The advantages in using this methodology are emphasized by an example of the multi-objective optimization design of suspension parameters and the results are compared with values reported in the literature and other gradient based and heuristic algorithms. The paper shows that the algorithm effectively leads to reliable results for suspension parameters with low computational effort. Research limitations/implications – The procedure is applied to a quarter car passive suspension design. Practical implications – The proposed procedure implies substantial time savings due to frequency domain analysis. Social implications – The paper proposes a procedure that allows complex optimization designs to be feasible and cost effective. Originality/value – The design optimization is performed in the frequency domain taking into account standard defined road profiles PSD without the need to simulate in the time domain.

Pareto-optimal front for multi-objective optimization of the suspension of a full-vehicle model in the frequency domain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Giovani Gaiardo Fossati ◽  
Letícia Fleck Fadel Miguel ◽  
Walter Jesus Paucar Casas
Keyword(s):  
Frequency Domain ◽  
Computational Time ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Vehicle Model ◽  
Content Type ◽  
Pareto Optimal Front ◽  
Multi Objective ◽  
Suspension Systems ◽  
Road Profile

PurposeThis study aims to propose a complete and powerful methodology that allows the optimization of the passive suspension system of vehicles, which simultaneously takes comfort and safety into account and provides a set of optimal solutions through a Pareto-optimal front, in a low computational time.Design/methodology/approachUnlike papers that consider simple vehicle models (quarter vehicle model or half car model) and/or simplified road profiles (harmonic excitation, for example) and/or perform a single-objective optimization and/or execute the dynamic analysis in the time domain, this paper presents an effective and fast methodology for the multi-objective optimization of the suspension system of a full-car model (including the driver seat) traveling on an irregular road profile, whose dynamic response is determined in the frequency domain, considerably reducing computational time.FindingsThe results showed that there was a reduction of 28% in the driver seat vertical acceleration weighted root mean square (RMS) value of the proposed model, which is directly related to comfort, and, simultaneously, an improvement or constancy concerning safety, with low computational cost. Hence, the proposed methodology can be indicated as a successful tool for the optimal design of the suspension systems, considering, simultaneously, comfort and safety.Originality/valueDespite the extensive literature on optimizing vehicle passive suspension systems, papers combining multi-objective optimization presenting a Pareto-optimal front as a set of optimal results, a full-vehicle model (including the driver seat), an irregular road profile and the determination of the dynamic response in the frequency domain are not found.

Multi-objective optimization of a spoke-type permanent magnet motor with fractional-slot concentrated windings for EVs

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Suying Liu ◽  
Jinlin Huang
Keyword(s):  
Optimization Design ◽  
Torque Ripple ◽  
Electrical Machine ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Driving System ◽  
Torque Density ◽  
Multi Objective ◽  
Lower Torque ◽  
Fractional Slot

Purpose This paper aims to propose a spoke-type fractional-slot concentrated windings (FSCW) PM machine for EVs driving system to improve torque density. To further improve electromagnetic performance, the multi-objective optimization design is processed based on response surface (RS) model and simulated annealing cuckoo search (SA-CS) algorithm. Design/methodology/approach The spoke-type FSCW PM machine is designed and optimized to meet the requirement of EVs driving system. First, a spoke-type FSCW PM machine is designed and some of key parameters are obtained based on equivalent magnetic circuit (EMC) method. Then, the RS model and modified SA-CS algorithm are proposed to obtain higher torque, lower torque ripple and higher efficiency. Findings After verification by finite element method for no-load and load performance, the optimal machine has higher torque density, lower torque ripple and higher efficiency compared with initial machine. Finally, a 20 kW prototype is manufactured and tested to verify the validity of the proposed optimization design method. Originality/value This paper designs a high torque density spoke-type FSCW PM machine, which is superior for EVs driving system. Meanwhile, a novel modified SA-CS algorithm is applied to the field of electrical machine multi-objective optimal design.

Multi-objective optimal design of double-sided switched reluctance linear generator for wave power generation

2019 ◽  
Vol 38 (6) ◽  
pp. 1948-1963
Author(s):  
Shuyan Zhao ◽  
Hao Chen ◽  
Rui Nie ◽  
Jinfu Liu
Keyword(s):  
Power Generation ◽  
Finite Element ◽  
Optimization Design ◽  
Wave Power ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Switched Reluctance ◽  
Multi Objective ◽  
Modified Entropy ◽  
Wave Power Generation

Purpose This paper aims to propose a double-sided switched reluctance linxear generator (DSRLG) exclusively for wave power generation. The initial dimensions are given through design experience and principles. To ameliorate comprehensive performance of the DSRLG, the multi-objective optimization design is processed. Design/methodology/approach The multi-objective optimization design of the DSRLG is processed by adopting a modified entropy technique for order of preference by similarity to ideal solution (TOPSIS) algorithm. First, sensitivity analyzes on geometric parameters of the DSRLG are conducted to determine several pivotal geometric parameters as optimization variables. Then, the multi-objective optimization is conducted on the basis of initial dimensions. After determination of synthetical evaluation value of each structure parameter, the best dimension scheme of the DSRLG is concluded. Findings After verification by finite element method simulation and dynamic simulation, the final dimension scheme proves to perform better than the initial scheme. Finally, experiments are conducted to verify the accuracy of both the stable finite element DSRLG model and dynamic simulation system model so that the conclusion of this paper proves to be reliable and compelling. Originality/value This paper proposes an improved structure of the DSRLG, which is superior for wave power generation. Meanwhile, a novel modified entropy TOPSIS algorithm is applied to the field of electrical machine multi-objective optimal design for the first time.

Multi-objective optimization design of engine crankshaft bearing

2016 ◽  
Vol 68 (1) ◽  
pp. 86-91 ◽  
Author(s):  
Jun Sun ◽  
Lei Shu ◽  
Xianhao Song ◽  
Guangsheng Liu ◽  
Feng Xu ◽  
...  
Keyword(s):  
Internal Combustion Engine ◽  
Power Loss ◽  
Optimization Design ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Engine Crankshaft ◽  
Bearing System

Purpose – This paper aims to use the crankshaft-bearing system of a four-cylinder internal combustion engine as the studying object, and develop a multi-objective optimization design of the crankshaft-bearing. In the current optimization design of engine crankshaft-bearing, only the crankshaft-bearing was considered as the studying object. However, the corresponding relations of major structure dimensions exist between the crankshaft and the crankshaft-bearing in internal combustion engine, and there are the interaction effects between the crankshaft and the crankshaft-bearing during the operation of internal combustion engine. Design/methodology/approach – The crankshaft mass and the total frictional power loss of crankshaft-bearing s are selected as the objective functions in the optimization design of crankshaft-bearing. The Particle Swarm Optimization algorithm based on the idea of decreasing strategy of inertia weight with the exponential type is used in the optimization calculation. Findings – The total frictional power loss of crankshaft-bearing and the crankshaft mass are decreased, respectively, by 26.2 and 5.3 per cent by the multi-objective optimization design of crankshaft-bearing, which are more reasonable than the ones of single-objective optimization design in which only the crankshaft-bearing is considered as the studying object. Originality/value – The crankshaft-bearing system of a four-cylinder internal combustion engine is taken as the studying object, and the multi-objective optimization design of crankshaft-bearing based on the crankshaft-bearing system is developed. The results of this paper are helpful to the design of the crankshaft-bearing for engine. There is universal significance to research the multi-objective optimization design of crankshaft-bearing based on the crankshaft-bearing system. The research method of the multi-objective optimization design of crankshaft-bearing based on the crankshaft-bearing system can be used to the optimization design of the bearing in the shaft-bearing system of ordinary machinery.

scholarly journals Multi-objective optimization design of bridge piers with hybrid heuristic algorithms

2012 ◽  
Vol 13 (6) ◽  
pp. 420-432 ◽  
Author(s):  
Francisco J. Martinez-Martin ◽  
Fernando Gonzalez-Vidosa ◽  
Antonio Hospitaler ◽  
Víctor Yepes
Keyword(s):  
Optimization Design ◽  
Heuristic Algorithms ◽  
Bridge Piers ◽  
Multi Objective Optimization ◽  
Hybrid Heuristic ◽  
Multi Objective

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

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