Multi-objective optimization of the suspension system parameters of a full vehicle model

In order to improve the riding and handling of the vehicle，the full-vehicle dynamical model of a certain vehicle is established by means of the software Adams/Car．The design of multi-objective optimization was used for Suspension system parameters on the base of the dynamical model．The optimized results show that riding of the vehicle is retained and dynamic load of wheel is improved obviously．It can be concluded that the optimization method is feasible for the optimization design of suspension system parameters．the investigation also supply the basis of theory for design considering the matching of the suspension system parameters.

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Multi-objective optimization of active suspension system in electric vehicle with In-Wheel-Motor against the negative electromechanical coupling effects

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2018.07.001 ◽

2019 ◽

Vol 116 ◽

pp. 545-565 ◽

Cited By ~ 12

Author(s):

Zhe Li ◽

Ling Zheng ◽

Yue Ren ◽

Yinong Li ◽

Zhoubing Xiong

Keyword(s):

Electric Vehicle ◽

Electromechanical Coupling ◽

Active Suspension ◽

Suspension System ◽

Multi Objective Optimization ◽

Coupling Effects ◽

Multi Objective

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Multi-objective optimization of a sports car suspension system using simplified quarter-car models

Mechanics & Industry ◽

10.1051/meca/2020039 ◽

2020 ◽

Vol 21 (4) ◽

pp. 412

Author(s):

Salman Ebrahimi-Nejad ◽

Majid Kheybari ◽

Seyed Vahid Nourbakhsh Borujerd

Keyword(s):

Numerical Solutions ◽

Suspension System ◽

Mode Shapes ◽

Ride Quality ◽

Multi Objective Optimization ◽

Multi Objective ◽

Characteristic Roots ◽

Design Variables ◽

Stiffness Matrices ◽

Quarter Car

In this paper, first, the vibrational governing equations for the suspension system of a selected sports car were derived using Lagrange's Equations. Then, numerical solutions of the equations were obtained to find the characteristic roots of the oscillating system, and the natural frequencies, mode shapes, and mass and stiffness matrices were obtained and verified. Next, the responses to unit step and unit impulse inputs were obtained. The paper compares the effects of various values of the damping coefficient and spring stiffness in order to identify which combination causes better suspension system performance. In this regard, we obtained and compared the time histories and the overshoot values of vehicle unsprung and sprung mass velocities, unsprung mass displacement, and suspension travel for various values of suspension stiffness (KS ) and damping (CS ) in a quarter-car model. Results indicate that the impulse imparted to the wheel is not affected by the values of CS and KS . Increasing KS will increase the maximum values of unsprung and sprung mass velocities and displacements, and increasing the value of CS slightly reduces the maximum values. By increasing both KS and CS we will have a smaller maximum suspension travel value. Although lower values of CS provide better ride quality, very low values are not effective. On the other hand, high values of CS and KS result in a stiffer suspension and the suspension will provide better handling and agility; the suspension should be designed with the best combination of design variables and operation parameters to provide optimum vibration performance. Finally, multi-objective optimization has been performed with the approach of choosing the best value for CS and KS and decreasing the maximum accelerations and displacements of unsprung and sprung masses, according to the TOPSIS method. Based on optimization results, the optimum range of KS is between 130 000–170 000, and the most favorable is 150, and 500 is the optimal mode for CS .

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Multi-objective optimization model in the vehicle suspension system development process

Tehnicki vjesnik - Technical Gazette ◽

10.17559/tv-20150220151816 ◽

2015 ◽

Vol 22 (4) ◽

pp. 1021-1028 ◽

Cited By ~ 2

Author(s):

Goran Šagi

Keyword(s):

Optimization Model ◽

Development Process ◽

System Development ◽

Suspension System ◽

Vehicle Suspension ◽

Multi Objective Optimization ◽

Multi Objective ◽

Vehicle Suspension System

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Use of nonlinear asymmetrical shock absorbers in multi-objective optimization of the suspension system in a variety of road excitations

Proceedings of the Institution of Mechanical Engineers Part K Journal of Multi-body Dynamics ◽

10.1177/1464419316671481 ◽

2016 ◽

Vol 231 (2) ◽

pp. 372-387 ◽

Cited By ~ 3

Author(s):

Abolfazl Seifi ◽

Reza Hassannejad ◽

Mohammad Ali Hamed

Keyword(s):

Degrees Of Freedom ◽

Ride Comfort ◽

Low Cost ◽

Suspension System ◽

Objective Functions ◽

Multi Objective Optimization ◽

Vehicle Handling ◽

Multi Objective ◽

Shock Absorbers ◽

The Impact

In this study, a new method to improve ride comfort, vehicle handling, and workspace was presented in multi-objective optimization using nonlinear asymmetrical dampers. The main aim of this research was to provide suitable passive suspension based on more efficiency and the low cost of the mentioned dampers. Using the model with five degrees of freedom, suspension system parameters were optimized under sinusoidal road excitation. The main functions of the suspension system were chosen as objective functions. In order to better illustrate the impact of each objective functions on the suspension parameters, at first two-objective and finally five-objective were considered in the optimization problem. The obtained results indicated that the optimized viscous coefficients for five-objective optimization lead to 3.58% increase in ride comfort, 0.74% in vehicle handling ability, and 2.20% in workspace changes for the average of forward and rear suspension.

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Optimization of the linear quadratic regulator (LQR) control quarter car suspension system using genetic algorithm

Ingeniería e Investigación ◽

10.15446/ing.investig.v36n1.49253 ◽

2016 ◽

Vol 36 (1) ◽

pp. 23-30 ◽

Cited By ~ 4

Author(s):

Mahesh Nagarkar ◽

G. J. Vikhe Patil

Keyword(s):

Genetic Algorithm ◽

Linear Quadratic Regulator ◽

Suspension System ◽

Optimization Approach ◽

Multi Objective Optimization ◽

Linear Quadratic ◽

Multi Objective ◽

Weighting Matrix ◽

Car Suspension ◽

Quarter Car

<p>In this paper, a genetic algorithm (GA) based in an optimization approach is presented in order to search the optimum weighting matrix parameters of a linear quadratic regulator (LQR). A Macpherson strut quarter car suspension system is implemented for ride control application. Initially, the GA is implemented with the objective of minimizing root mean square (RMS) controller force. For single objective optimization, RMS controller force is reduced by 20.42% with slight increase in RMS sprung mass acceleration. Trade-off is observed between controller force and sprung mass acceleration. Further, an analysis is extended to multi-objective optimization with objectives such as minimization of RMS controller force and RMS sprung mass acceleration and minimization of RMS controller force, RMS sprung mass acceleration and suspension space deflection. For multi-objective optimization, Pareto-front gives flexibility in order to choose the optimum solution as per designer’s need.</p>

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Multi-objective optimization of a hybrid electromagnetic suspension system for ride comfort, road holding and regenerated power

Journal of Vibration and Control ◽

10.1177/1077546315585219 ◽

2016 ◽

Vol 23 (5) ◽

pp. 782-793 ◽

Cited By ~ 20

Author(s):

Mansour Ataei ◽

Ehsan Asadi ◽

Avesta Goodarzi ◽

Amir Khajepour ◽

Mir Behrad Khamesee

Keyword(s):

Pareto Front ◽

Ride Comfort ◽

Optimization Method ◽

Suspension System ◽

Multi Objective Optimization ◽

Damping Force ◽

Nsga Ii ◽

Electromagnetic Suspension ◽

Multi Objective ◽

Electromagnetic Component

This paper reports work on the optimization and performance evaluation of a hybrid electromagnetic suspension system equipped with a hybrid electromagnetic damper. The hybrid damper is configured to operate with hydraulic and electromagnetic components. The hydraulic component produces a large fail-safe baseline damping force, while the electromagnetic component adds energy regeneration and adaptability to the suspension. For analyzing the system, the electromagnetic component was modeled and integrated into a 2DOF quarter-car model. Three criteria were considered for evaluating the performance of the suspension system: ride comfort, road holding and regenerated power. Using the genetic algorithm multi-objective optimization (NSGA-II), the suspension design was optimized to improve the performance of the vehicle with respect to the selected criteria. The multi-objective optimization method provided a set of solutions called Pareto front in which all solutions are equally good and the selection of each one depends on conditions and needs. Among the given solutions in the Pareto front, a small number of cases, with different design purposes, were selected. The performances of the selected designs were compared with two reference systems: a conventional and a nonoptimized hybrid suspension system. The results show that the ride comfort and road holding qualities of the optimized hybrid system are improved, and the regenerated power is considerably increased.

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

Engineering Computations ◽

10.1108/ec-12-2020-0724 ◽

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.

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