Research on Load Estimation for Commercial Trucks Based on Air Suspension State Parameters

Abstract

For commercial trucks, accurate vehicle load information is crucial to preventing overloading and uneven load distribution, thereby improving transportation efficiency and reducing transportation costs. Existing research on vehicle load estimation primarily focuses on tires, axles, frames, and leaf springs, with limited studies on load estimation for vehicles equipped with air suspension. This paper presents the design of a vehicle onboard weighing system for civil commercial trucks based on the state parameters of air springs and proposes a matching method for vehicle load estimation. The system utilizes laser distance- and gas pressure sensors to collect the state parameters of the air springs. It estimates the vehicle load and displays the load information in real time on the onboard display. The vehicle load estimation method was explored through prototype testing and theoretical derivation. A fitting model was constructed using surface fitting techniques to establish the relationship between the effective contact area and the height variation and capsule pressure of the air spring. Subsequently, a load prediction model was built based on the force equilibrium equation of the air springs. Finally, the construction and accuracy of the load prediction model for a specific type of diaphragm air spring were verified using finite element analysis. The results demonstrated that the average relative error of the load prediction model could be controlled within 1%, meeting the high accuracy requirements of the vehicle weighing system.