Multi-objective traction optimization of vehicles in loose dry sand using the generalized reduced gradient method. (April 2016)

• Record Type: Journal Article
• Authors: Robinson, Joe D.; Vahedifard, Farshid; Rais-Rohani, Masoud; Mason, George L.; Priddy, Jody D.
• Is Part Of: Journal of terramechanics. Volume 64(2016:Apr.)
• Page Start: 46
• Page End: 57
• Publication Date: 2016-04
• Subjects: Mobility -- Vehicle terrain interface (VTI) model -- Drawbar pull (DBP) coefficient -- Work optimum coefficient (WOC) -- Multi-objective optimization; Trafficability -- Periodicals; Praticabilité (Routes) -- Périodiques; Trafficability; Periodicals; 629.222
• DOI: 10.1016/j.jterra.2015.12.005
• Languages: English
• ISSNs: 0022-4898

Abstract

Highlights: Tractive performance of a multi-wheeled vehicle operating on loose dry sand is optimized. The generalized reduction gradient method is used to optimize traction control parameters. The work optimum of each tire is maximized to find a set of Pareto optimal solutions. A method to apply the optimization results for predicting vehicle performance is presented. Abstract: A work optimization strategy is combined with algorithms within the vehicle-terrain interface (VTI) model to maximize the traction of a four-wheel vehicle operating on loose dry sand. The optimization model distributes traction among the steered and non-steered wheels with the work optimum coefficient ( WOC ) of each wheel treated as an independent design objective. Drawbar pull ( DBP ), motion resistance ( MR ), longitudinal traction coefficient ( LTC ), lateral force coefficient ( LFC ), tire deflection, and wheel slip are key parameters that appear in the VTI model for traction performance analysis. The analysis includes wheels of different diameters, widths, heights, and inflation pressures, under variable wheel slips. A multi-objective optimization problem is formulated over a thirteen-dimensional search space bounded by eight design constraints. The generalized reduced gradient method is used to predict optimal values of the design variables as well as ground and traction parameters such as DBP, MR, LTC, and LFC for maximum slope climbing efficiency. The WOCs are maximized for lateral slip angles between 0° and 24° to find a set of Pareto optimal solutions over a wide range of weight factors. A method to apply the optimization results for predicting vehicle performance and traction control on dry sand is presented and discussed.