Topic
Vehicle dynamics
About: Vehicle dynamics is a research topic. Over the lifetime, 12909 publications have been published within this topic receiving 204091 citations.
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TL;DR: The design of a novel active safety system preventing unintended roadway departures and results demonstrate the capability of the proposed controller to detect and avoid roadway departures while avoiding unnecessary interventions.
Abstract: This paper presents the design of a novel active safety system preventing unintended roadway departures. The proposed framework unifies threat assessment, stability, and control of passenger vehicles into a single combined optimization problem. A nonlinear model predictive control (MPC) problem is formulated, where nonlinear vehicle dynamics, in closed-loop with a driver model, is used to optimize the steering and braking actions needed to keep the driver safe. A model of the driver's nominal behavior is estimated based on his observed behavior. The driver commands the vehicle, whereas the safety system corrects the driver's steering and braking actions in case there is a risk that the vehicle will unintentionally depart from the road. The resulting predictive controller is always active, and mode switching is not necessary. We show simulation results detailing the behavior of the proposed controller and experimental results obtained by implementing the proposed framework on embedded hardware in a passenger vehicle. The results demonstrate the capability of the proposed controller to detect and avoid roadway departures while avoiding unnecessary interventions.
115 citations
TL;DR: This paper develops an output feedback adaptive neural network (NN) control incorporating a linear dynamic compensator to achieve stable dynamic balance and tracking of the desired given trajectories and proves the efficiency of the developed nonlinear controller.
Abstract: The wheeled inverted pendulum (WIP) models have been widely applied in the transportation vehicles formed by a mobile wheeled inverted pendulum system with an operator (demonstrated in Fig. 1 ). In this paper, we focus on the study of nonlinear control design for the WIP model-based vehicles, for which accurate dynamics could not be obtained beforehand due to the presence of uncertainties caused by the human operator as well as the vehicle. We develop an output feedback adaptive neural network (NN) control incorporating a linear dynamic compensator to achieve stable dynamic balance and tracking of the desired given trajectories. Comparison simulation studies demonstrate guaranteed tracking performance and stable dynamics balance in the presence of uncertainties and thus verify the efficiency of the developed nonlinear controller.
115 citations
08 Jun 2005
TL;DR: In this article, the authors investigate the use of a nonlinear control allocation scheme for automotive vehicles, where a higher level control system specifies a desired moment to work on the vehicle, while the control allocation distributes this moment among the individual wheels by commanding appropriate wheel slips.
Abstract: We investigate the use of a nonlinear control allocation scheme for automotive vehicles. Such a scheme is useful in e.g. yaw or roll stabilization of the vehicle. The control allocation allows a modularization of the control task, such that a higher level control system specifies a desired moment to work on the vehicle, while the control allocation distributes this moment among the individual wheels by commanding appropriate wheel slips. The control allocation problem is defined as a nonlinear optimization problem, to which an explicit piecewise linear approximate solution function is computed off-line. Such a solution function can computationally efficiently be implemented in real time with at most a few hundred arithmetic operations per sample. Yaw stabilization of the vehicle yaw dynamics is used as an example of use of the control allocation. Simulations show that the controller stabilizes the vehicle in an extreme manoeuvre where the vehicle yaw dynamics otherwise becomes unstable.
115 citations
TL;DR: In this article, the Polynomial-Chaos-Chebyshev-Interval (PCCI) method is proposed for vehicle dynamics involving hybrid uncertainty parameters. But the PCCI method is non-intrusive, because it does not require the amendment of the original solver for different and complicated dynamics problems.
114 citations
TL;DR: This paper presents a method for electronic stability control based on model predictive control (MPC) using the bicycle model with lagged tire force to reflect the lagged characteristics of lateral tire forces on the prediction model of the MPC problem for better description of the vehicle behavior.
Abstract: This paper presents a method for electronic stability control (ESC) based on model predictive control (MPC) using the bicycle model with lagged tire force to reflect the lagged characteristics of lateral tire forces on the prediction model of the MPC problem for better description of the vehicle behavior. To avoid the computational burden in finding the optimal solution of the MPC problem using the constrained optimal control theory, the desired states and inputs as references are generated since the solution of the MPC problem can be easily obtained in a closed form without using numeric solvers using these reference values. The suggested method controls the vehicle to follow the generated reference values to maintain the vehicle yaw stability while the vehicle turns as the driver intended. The superiority of the proposed method is verified through comparisons with an ESC method based on ordinary MPC in the simulation environments on both high- and low- μ surfaces using the vehicle dynamics software CarSim.
114 citations