Vehicle dynamics

About: Vehicle dynamics is a research topic. Over the lifetime, 12909 publications have been published within this topic receiving 204091 citations.

Large motion control of mobile manipulators including vehicle suspension characteristics

Abstract: Conventional fixed-base controllers are shown not to perform well on mobile manipulators due to the dynamic interactions between a manipulator and its vehicle. An extended Jacobian transpose control algorithm is developed to improve the performance of such manipulator systems. It is shown to perform well in the presence of modeling errors and the practical limitations imposed by the sensory information available for control in highly unstructured field environments. >

Eco-Departure of Connected Vehicles With V2X Communication at Signalized Intersections

Abstract: Eco-driving at signalized intersections has significant potential for energy saving. In this paper, we focus on eco-departure operations of connected vehicles equipped with an internal combustion engine and a step-gear automatic transmission. A Bolza-type optimal control problem (OCP) is formulated to minimize engine fuel consumption. Due to the discrete gear ratio, this OCP is a nonlinear mixed-integer problem, which is challenging to handle by most existing optimization methods. The Legendre pseudospectral method combining the knotting technique is employed to convert it into a multistage interconnected nonlinear programming problem, which then solves the optimal engine torque and transmission gear position. The fuel-saving benefit of the optimized eco-departing operation is validated by a passenger car with a five-speed transmission. For real-time implementation, a near-optimal departing strategy is proposed to quickly determine the behavior of the engine and transmission. When a string of vehicles are departing from an intersection, the acceleration of the leading vehicle(s) should be considered to control the following vehicles. This issue is also addressed in this paper.

Estimation of track-soil interactions for autonomous tracked vehicles

Abstract: Real time estimation of soil parameters is essential in achieving precise, robust autonomous guidance and control of a tracked vehicle. The paper shows that the slip of the tracks over the terrain can be identified from trajectory data using an extended Kalman filter. The use of a suitable soil model can then allow key soil parameters to be estimated as the vehicle passes over the soil. Knowledge of the soil parameters may in turn be used to allow reference trajectories and control algorithms to be adjusted to suit the soil conditions.

Estimation of absolute vehicle speed using fuzzy logic rule-based Kalman filter

Abstract: Accurate knowledge on the absolute or true speed of a vehicle, if and when available, can be used to enhance advanced vehicle dynamics control systems such as anti-lock brake systems (ABS) and auto-traction systems (ATS) control schemes. Current conventional method uses wheel speed measurements to estimate the speed of the vehicle. As a result, indication of the vehicle speed becomes erroneous and, thus, unreliable when large slips occur between the wheels and terrain. This paper describes a fuzzy rule-based Kalman filtering technique which employs an additional accelerometer to complement the wheel-based speed sensor, and produce an accurate estimation of the true speed of a vehicle. We use the Kalman filters to deal with the noise and uncertainties in the speed and acceleration models, and fuzzy logic to tune the covariances and reset the initialization of the filter according to slip conditions detected and measurement-estimation condition. Experiments were conducted using an actual vehicle to verify the proposed strategy.