Session: 08-01-01: General Dynamics, Vibration, and Control I

Paper Number: 165894

The Effect of Sprung Masses on Drive Control and Stability of HOWO 6×4371HP RHD Dump Truck 

The study focuses on sprung mass effects on drive control and stability of the HOWO 6×4 371hp Right-Hand Drive (RHD) Dump Truck-a vehicle widely used in the world for construction, mining, and transport. Since the vehicle has been in frequent accidents due to its high center of gravity and its loading configuration, the optimization of vehicle dynamics in the interest of safety. It seeks the evaluation of the changes of sprung mass effect on center of gravity (CG), mass moment of inertia (I), and overall stability during cornering, accelerate, or decelerate maneuvers. By employing robust mathematical modeling, it advances the understanding of the dynamics of heavy vehicles while yielding working practical recommendations for enhancing suspension design, load distribution, and control systems in challenging operating conditions.
Methodology comprises a nonlinear four-degree-of-freedom dynamic model, taking parameters like that of CG of the truck, principal mass moments of inertia, and active suspension control into account. CG has been calculated with the help of geometric and load measurements, showing a longitudinal position of 3240 mm, registering as transverse at 0 mm (aligned on the vertical symmetry pathway) and at a vertical height of 2022.9 mm. The data relate to the truck's payload capacity, which due to its high CG is likely to lead to a rollover if proper management of weight distribution is not done. The mass moment of inertia tensor is based on theorems of parallel and perpendicular axis. Its eigenvalues, 1407×10^3 kgm^2, 532.3×10^3 kgm^2, and -270.8×10^(3 ) kgm^2, show grand resistance to rotational perturbations regarding the longitudinal lateral and vertical axes. Eigenvector analysis clearly describes the orientation of principal axes, emphasizing its stability against pitching, rolling, and yawing.
This work introduces a remarkable innovation-a combination of an active suspension system and fuzzy-PID controlled strategy to dynamically adjust the suspension parameters to counteract the rolling motions during lifting of the cargo and traversing uneven terrain. The comparison of various simulations indicated that the fuzzy-PID controller was superior to traditional PID control. It provided better stability, roll angles, and improved performance in deviating from disturbances. The control work produced a reverse roll moment to cancel out the instability, which was also confirmed in a nonlinear roll matrix model taking into indicatively cargo dynamics, suspension forces, and tire-road contact.
Key findings underscore the importance of CG optimization and sprung mass management. The proposed tolerances, longitudinal CG capped at 3400 mm, lateral CG within ±100 mm of the symmetry plane, and sprung mass maintained within ±5% of nominal values, ensure balanced handling and reduced rollover risks. The active suspension system reduced roll angles by 30–40% during dynamic maneuvers, significantly enhancing driver safety and payload stability. Additionally, the study highlights the interplay between high sprung mass, increased moment of inertia, and energy demands during rotational motions, necessitating trade-offs between stability and maneuverability in design practices.
In conclusion, this research advances heavy vehicle engineering by establishing a robust analytical framework for CG and inertia analysis, coupled with adaptive control strategies. The results demonstrate that precise CG positioning, optimized load distribution, and active suspension systems are pivotal for mitigating accidents and improving operational safety. Future work should explore real-world validation of the model and expand its application to diverse heavy-duty vehicles, fostering broader advancements in vehicular dynamics and intelligent transportation systems.
Keywords: Sprung Masses, Vehicle Dynamics, Center of Gravity, Moment of Inertia, Fuzzy-PID Control.

Presenting Author: Ammar Alsheghri King Fahd University of Petroleum and Minerals (KFUPM)

Presenting Author Biography: Dr. Ammar Alsheghri is an Assistant Professor in the Department of Mechanical Engineering at King Fahd University of Petroleum & Minerals (KFUPM). He completed his PhD from the Department of Mining and Materials Engineering and the Faculty of Dentistry of McGill University, where his work focused on biomaterials and advanced composites for biomedical applications.
Dr. Alsheghri’s research interests span intelligent manufacturing, artificial intelligence applications in engineering, Modeling and FEA, bioinformatics, biomaterials, polymer composites, and bioengineering. His interdisciplinary expertise bridges materials science and biomedical engineering, with a focus on developing innovative scaffolds and functional materials for tissue engineering and regenerative medicine. He has published over 20 peer-reviewed articles.
At KFUPM, Dr. Alsheghri leads projects on smart hydrogel inks for 3D-printing biomaterials, fracture modelling of bone-inspired composites, and automated systems for dental applications. His work contributes to advancing the fields of materials engineering, biomedical technology, and sustainable health solutions through cutting-edge research and innovation.

Authors:

Ermias Wubete Fenta King Fahd University of Petroleum and Minerals
Ammar Alsheghri King Fahd University of Petroleum and Minerals (KFUPM)
Girma Tsegaye Tefera Debre Markos University
Amare Addis Wondyifraw Debre Markos University