Ride Comfort Analysis and Multivariable Co-Optimization of the Commercial Vehicle Based on an Improved Nonlinear Model

Keren Chen,Rongjiang Tang,Enyong Xu,Weiguang Zheng,Shuilong He

doi:10.1109/access.2019.2962522

Keren Chen, Rongjiang Tang + Show 3 more

Open Access

https://doi.org/10.1109/access.2019.2962522

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Abstract

The performance of a suspension system is affected by the behavior and posture of its components. However, published studies usually conduct this research using the based-equivalent model without considering the characteristic curves or postures. In this paper, an improved ride comfort model that considers three nonlinearities in suspensions is first developed, and this model is validated through experimental results and demonstrates good accuracy. Then, the dynamic response is presented to investigate the effects of multilevel suspension parameters and nonlinear factors on ride comfort, and it is concluded that the front chassis suspension is the most significant system for ride comfort. Next, a multivariable co-optimization method based on the improved model is proposed to obtain more accurate optimized results that are more suitable for automotive applications. Subsequently, a multiobjective genetic algorithm (MGA) is applied to obtain the Pareto solution set. Furthermore, comparing the RMS value before and after optimization shows an obvious reduction, with averages of 19.7%, 17.8%, and 12.0% for the weighted root mean square (RMS) of the driver seat acceleration and the RMS of the working spaces of the front chassis suspension and the rear chassis suspension, respectively. Finally, the results are also verified by experiments, indicating that the improved ride comfort model and the multivariable co-optimization method are feasible and practical.

Highlights

Ride comfort plays an important role in evaluating vehicle performance [1], [2] and has been an interesting topic for researchers [3]
Suspension systems are of great importance in determining ride comfort and are mainly designed to isolate the frame and passengers from road excitation [6], [7]
To optimize ride comfort at the common speed to the greatest extent possible, the weighted root mean square (RMS) value of the vertical acceleration of driver seat and the RMS value of the suspension working space travelling at 30 km/h, 60 km/h, and 90 km/h are selected as the optimization indexes

Summary

INTRODUCTION

Ride comfort plays an important role in evaluating vehicle performance [1], [2] and has been an interesting topic for researchers [3]. The contributions of this study are as follows: (a) an improved ride comfort model for a commercial vehicle is proposed based on these nonlinearities, including the nonlinear characteristics of the damper force, the posture of the suspension components, and the damper location of the balanced suspension; and (b) a co-optimization method for ride comfort is designed based on multivariable. Three nonlinear factors of commercial vehicle suspension, namely, the nonlinear characteristics of the damper force, the posture of the suspension components, and the damper location of the balanced suspension, are first discussed and modeled through equations These equations are applied to the conventional vibration model to develop the improved ride comfort model, which is validated using the experimental results. Where λ is the scale factor; η is the asymmetry coefficient, which indicates the difference between the compression and extension coefficient; and n is the damping characteristic index

BALANCED SUSPENSION MODEL

CABIN SUSPENSION MODEL

BIVARIATE ANALYSIS BASED ON THE IMPROVED RIDE COMFORT MODEL

OPTIMIZATION RESULTS

VIII. CONCLUSION