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Lateral dynamic control considered to be crucial to enhance the handling characteristics and stabilization of a vehicle as a safety demand. In this paper, active rear axles steering control system will be developed using an optimal quadratic regulator (LQR) control methodology. The controller aims to minimize the vehicle side slip and consequently increase its handling stability and transient state performance. The controller design has been utilized the independent steering of the vehicle’s 3rd and 4th axles as control inputs. Furthermore, the developed controller will be combined with a feedforward zero side slip (ZSS) controller based on the steady-state model of the vehicle and satisfying the Ackermann steering condition. In addition, the steady-state handling performance will be evaluated using the Skid Pad test.

Off-road vehicle performance of a multi-wheeled 8×8 combat vehicle is strongly affected by the tire-terrain interaction characteristics. Soft soil reduces traction and modifies vehicle handling; therefore tire dynamics play a strong role in off-road mobility evaluation. In this paper three-dimensional, non-linear Finite Element Analysis (FEA) off-road tire models are developed using PAM-CRASH and the general trends of vertical load-deflection, cornering characteristics and aligning moment on rigid terrains are predicted and compared with published, measured data of a similar tire for validation purposes. The FEA off-road tire models are used to investigate the multi-pass behavior of the wheels running and steering on soft terrain. The steering characteristics of the multi-wheels are also predicted for the purpose of the development of tire-soft soil empirical equations for future research work.

The objective of the Integrated Chassis Controllers (ICC) is to combine multiple actuators and dynamics controllers to maximize the overall vehicle performance at all driving conditions. It is well known that there are two methods that can be used to develop an ICC. The first is a centralized method, where all the actuators are considered in one controller to ensure a harmonic integration between different actuators. The second method is called decentralized integration, where each actuator is considered in a separate controller and a low-level controller is used to coordinate the operation of the controllers. In this paper, the second method is used to develop a decentralized ICC using a novel controller coordinator based on Genetic Programming (GP). The GP is used to integrate torque vectoring and active rear steering controllers of an 8x8 combat vehicle. The controller is utilized to enhance the lateral stability of the vehicle in various driving conditions.

This work investigates the steering and wheel speed control of a completely custom built 8x8 scaled electric combat vehicle (SECV) which has been constructed to meet the Ackermann condition at low speeds. During remote control operation the scaled vehicle is capable of continuously maintaining and varying the individual wheel speed and individual wheel steering angles of all eight wheels in real time. Several steering scenarios have been developed including traditional (front 2-axle steering), fixed third axle (first, second and fourth axle steering), all wheel steering and crab steering (all wheels are parallel with same steering angle). The traditional, two axle steering scenario is experimentally tested for accuracy in this work with planned future research for experimental analysis of the other steering configurations. This work is conducted using Arduino software to control the physical SECV and TruckSim software to simulate the dynamics of the vehicle.

This paper proposes an active chassis control strategy for an Eight-wheel drive/Four-wheel steering (8WD/4WS) combat vehicle, where only the first and second axles’ wheels are steerable, while the third and fourth axles’ wheels are non-steerable. Utilizing torque vectoring and differential braking control to improve its lateral dynamics at limit handling. Due to the non-linear characteristics of the tires and its friction limit, the vehicle may exhibit instable behavior during cornering maneuvers. It is well known that the tire longitudinal and lateral forces are shared, if longitudinal forces increased, slip ratio will increase and causing reduction in lateral forces that may cause the vehicle to drift out or spinning. Accordingly, the tires forces need to be optimally distributed based on vertical loads for each tire to prevent it from reaching the friction limit based on Friction Ellipse Theorem.

With the rise in demand, advanced steering control and electric vehicle technology are rapidly developing in modern times. Due to a controller's role as a backbone for the modern vehicle, its study has become increasingly crucial. This research proposes a novel 4th axle steering (4AS) feedforward controller that utilizes the first, second and fourth axle steering control for an 8x8 scaled electric combat vehicle. The vehicle is tested using the predefined path following. The novel 4AS controller is then compared to the Ackermann steering condition at different speeds. In the scaled vehicle used for this research, each wheel is independently driven by an in-wheel motor, while the steering is carried out by linear actuators. Individual eight-wheel steering control systems are designed and installed on the scaled vehicle to evaluate the driving performance from low speed to high speed. The 4AS steering method is implemented to improve the stability of the scaled vehicle at high speeds.