PAYLOAD PARAMETER REAL-TIME ESTIMATION FOR LIGHTWEIGHT VEHICLES

This paper proposes a payload parameter estimation method for lightweight vehicles (LWVs), whose dynamics and control are substantially affected by their payload variations due to the LWVs' significantly reduced sizes and weights. Accurate and real-time estimation of payload parameters, including payload mass and its onboard planar location, will be helpful for controller designs and load condition monitoring. The proposed payload parameter estimator (PPE) is divided into two parts: tire nominal normal force estimator (NNFE) based on a recursive least squares (RLS) algorithm using signals measured from LWV constant speed maneuvers, and parameter calculator based on estimated nominal normal forces. The prototype LWV is an electric ground vehicle with separable torque control of the four wheels by in-wheel motors, which allow redundant input injections in the designed maneuvers. Simulation results, based on a CarSim (R) model, show that the proposed PPE is capable of accurately and quickly estimating payload parameters, and is independent of the road condition as long as the tire forces are kept within their linear ranges.