Multi-objective Optimization of Hedge-Algebra-Based Controllers for Quarter-Car Active Suspension Models

2021 ◽  
pp. 876-885
Author(s):  
Hai-Le Bui
Keyword(s):  
Active Suspension ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Quarter Car ◽  
Suspension Models

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

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 .

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

2016 ◽  
Vol 36 (1) ◽  
pp. 23-30 ◽  
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>

The Influence of Tire Damping in Quarter Car Active Suspension Models

1991 ◽  
Vol 113 (1) ◽  
pp. 134-137 ◽  
Author(s):  
J. A. Levitt ◽  
N. G. Zorka
Keyword(s):  
Damping Ratio ◽  
Active Suspension ◽  
Vertical Acceleration ◽  
Body Acceleration ◽  
Suspension Systems ◽  
Active Suspension Systems ◽  
Quarter Car ◽  
Control Forces ◽  
And Control ◽  
Suspension Models

Setting tire damping to zero when modeling automotive active suspension systems compels the misleading conclusions that, at the wheelhop frequency, no matter what forces are exerted between sprung and unsprung masses, their motion are uncoupled, and the vertical acceleration of the sprung mass will be unaffected. Alternatively, taking tire damping to be small but nonzero, the motions of the sprung and unsprung masses are coupled at all frequencies, and control forces can be used to reduce the sprung mass vertical acceleration at the wheelhop frequency. The effect of introducing tire damping can be quite large. In the case of a force law chosen to enhance ride along a straight smooth road, where road holding is not a major concern, setting the tire damping ratio to 0.02 reduces rms body acceleration by 30 percent.

Influence of Tire Damping on Actively Controlled Quarter-Car Suspensions

2011 ◽  
Vol 133 (5) ◽  
Author(s):  
Hüseyin Akçay ◽  
Semiha Türkay
Keyword(s):  
Linear Matrix ◽  
Multi Objective ◽  
Quarter Car Model ◽  
Suspension Systems ◽  
Objective Control ◽  
Parametric Studies ◽  
Nonconvex And Nonsmooth Optimization ◽  
Quarter Car ◽  
Order Restricted ◽  
Suspension Models

In this note, a comprehensive analysis of tire damping effect on H2-optimal, multi-objective, and robust control of quarter-car suspensions excited by random road disturbances is provided. First, H2-optimal and convex multi-objective control problems are formulated and the latter problem is solved using linear matrix inequalities. Next, the multi-objective control problem is reformulated as a nonconvex and nonsmooth optimization problem with controller order restricted to be less than or equal to the quarter-car model order. For a range of orders, controllers are synthesized by using the HIFOO toolbox. Parametric studies of this note show that the effect of tire damping on the closed-loop performance of actively controlled suspension systems can be significant. Lastly, a robust controller with guaranteed performance over all polytopic suspension models with tire damping coefficient confined to a prescribed interval is synthesized.

scholarly journals Multi-Objective Optimization of Nonlinear Quarter Car Suspension System – PID and LQR Control

2018 ◽  
Vol 20 ◽  
pp. 420-427 ◽  
Author(s):  
MP Nagarkar ◽  
YJ Bhalerao ◽  
GJ Vikhe Patil ◽  
RN Zaware Patil
Keyword(s):  
Suspension System ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Lqr Control ◽  
Car Suspension ◽  
Quarter Car

Multi objective optimization of quarter car parameters for better ride comfort and road holding

2019 ◽  
Author(s):  
N. P. Puneet ◽  
Abhinandan Hegale ◽  
Hemantha Kumar ◽  
K. V. Gangadharan
Keyword(s):  
Ride Comfort ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Quarter Car
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