A Multi Objective Optimization Approach to Optimize Vehicle Ride and Handling Characteristics
Vehicle suspension design must fulfill
some conflicting criteria. Among those is ride comfort
which is attained by minimizing the acceleration
transmitted to the sprung mass, via suspension spring
and damper. Also good handling of a vehicle is a
desirable property which requires stiff suspension and
therefore is in contrast with a vehicle with good ride.
Among the other desirable features of a suspension is
the minimization of the maximum travel of suspension.
This travel which is called suspension working space in
vehicle dynamics literature is also a design constraint
and it favors good ride. In this research a full car 8
degrees of freedom model has been developed and the
three above mentioned criteria, namely: ride, handling
and working space has been adopted as objective
functions. The Multi Objective Programming (MOP)
discipline has been used to find the Pareto Front and
some reasoning used to chose a design point between
these non dominated points of Pareto Front.
[1] Guide for Evaluation of Human Exposure to Whole-Body Vibration,
2nd ed., International Standard 2631-1978(E), International
Organization for Standardization, 1978.
[2] Emanuele Guglielmino, et al (2008) Semi Active Suspension Control.
Springer-Verlag London.
[3] Mohamed Bouazara, Marc J. Richard, "An optimization method
designed to improve 3-D vehicle comfort and road holding capability
through the use of active and semi-active suspensions" Eur. J. Mech.
A/Solids 20 (2001) 509-520.
[4] Coello Coello, C.A., Van Veldhuizen, D.A., and Lamont, G.B. (2002)
Evolutionary Algorithms for Solving Multi-objective problems. Kluwer
Academic Publishers, NY.
[5] N. Srinivas and Kalyanmoy Deb. Multiobjective Optimization Using
Nondominated Sorting in Genetic Algorithms. Evolutionary
Computation, 2(3):221 - 248, 1994.
[6] Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and T. Meyarivan. A
Fast Elitist Multi-objective Genetic Algorithm: NSGA-II. IEEE
Transactions on Evolutionary Computation, 6(2):182 - 197, April 2002.
[1] Guide for Evaluation of Human Exposure to Whole-Body Vibration,
2nd ed., International Standard 2631-1978(E), International
Organization for Standardization, 1978.
[2] Emanuele Guglielmino, et al (2008) Semi Active Suspension Control.
Springer-Verlag London.
[3] Mohamed Bouazara, Marc J. Richard, "An optimization method
designed to improve 3-D vehicle comfort and road holding capability
through the use of active and semi-active suspensions" Eur. J. Mech.
A/Solids 20 (2001) 509-520.
[4] Coello Coello, C.A., Van Veldhuizen, D.A., and Lamont, G.B. (2002)
Evolutionary Algorithms for Solving Multi-objective problems. Kluwer
Academic Publishers, NY.
[5] N. Srinivas and Kalyanmoy Deb. Multiobjective Optimization Using
Nondominated Sorting in Genetic Algorithms. Evolutionary
Computation, 2(3):221 - 248, 1994.
[6] Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and T. Meyarivan. A
Fast Elitist Multi-objective Genetic Algorithm: NSGA-II. IEEE
Transactions on Evolutionary Computation, 6(2):182 - 197, April 2002.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:56034", author = "Mehrdad N. Khajavi and Bahram Notghi and Golamhassan Paygane", title = "A Multi Objective Optimization Approach to Optimize Vehicle Ride and Handling Characteristics", abstract = "Vehicle suspension design must fulfill
some conflicting criteria. Among those is ride comfort
which is attained by minimizing the acceleration
transmitted to the sprung mass, via suspension spring
and damper. Also good handling of a vehicle is a
desirable property which requires stiff suspension and
therefore is in contrast with a vehicle with good ride.
Among the other desirable features of a suspension is
the minimization of the maximum travel of suspension.
This travel which is called suspension working space in
vehicle dynamics literature is also a design constraint
and it favors good ride. In this research a full car 8
degrees of freedom model has been developed and the
three above mentioned criteria, namely: ride, handling
and working space has been adopted as objective
functions. The Multi Objective Programming (MOP)
discipline has been used to find the Pareto Front and
some reasoning used to chose a design point between
these non dominated points of Pareto Front.", keywords = "Vehicle, Ride, Handling, Suspension,Working Space, Multi Objective Programming.", volume = "4", number = "2", pages = "202-5", }