Abstract
Ride comfort and handling performances are known conflicts for off-road vehicles. Recent publications focus on passenger vehicles on class B and class C roads, while, for off-road vehicles, they should be able to run on rougher roads: class D, class E, or class F roads. In this paper, a quarter vehicle model with nonlinear damping is established to analyze the suspension performance of a medium off-road vehicle on the class F road. The ride comfort, road holding, and handling performance of the vehicle are indicated by the weighted root mean square (RMS) value of the vertical acceleration of the sprung mass, suspension travel, and tire deflection. To optimize these objectives, the genetic algorithm (GA), particle swarm optimization (PSO), and a genetic algorithm based on the particle swarm optimization (GA-PSO) are initiated. The efficiency and accuracy of these algorithms are compared to find the best suspension parameters. The effect of the optimized method is validated by the field test result. The ride comfort, road holding, and handling performance are improved by approximately 20%.
Highlights
Ride comfort and handling performances are known conflicts for off-road vehicles
The genetic algorithm (GA), particle swarm optimization (PSO), and a genetic algorithm based on the particle swarm optimization (GA-PSO) are initiated. e efficiency and accuracy of these algorithms are compared to find the best suspension parameters. e effect of the optimized method is validated by the field test result. e ride comfort, road holding, and handling performance are improved by approximately 20%
Yang proposed an improved genetic algorithm based on fitness evaluation to analyze the ride comfort of an in-wheel motor vehicle on the class B road; the root mean square (RMS) value of the vehicle weighted vertical acceleration and the pitching angle acceleration are taken as the objectives [3]. e PSO is initiated in Li’s research [4] and an improved GA named KEMOGA is provided [5] to Mathematical Problems in Engineering optimize the ride comfort of the passenger vehicle on class B and class C roads. ey all take the RMS of the weight vertical acceleration, suspension travel, and tire deflection as their objectives
Summary
To verify the effect of the quarter vehicle model, the field test on the class F road is carried out in the Dingyuan test field. Since the parameters of the quarter vehicle are the equivalent value of the rear suspension, the sensors are mounted on the rear right suspension. E tested and simulated acceleration signals on the upper suspension mount and lower arm are shown in Figures 6 and 7. E error of the lower arm acceleration is caused by taking the tire as a linear spring model.
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