Search Results

This paper presents the algorithm for a Kalman filter active vehicle suspension design. Based on simulations, two main issues have been investigated, (a) the effects of disturbances from the changes in road input and the variations of vehicle parameters on state observer estimation, (b) the benefits of adaptation of an active suspension to the changes of road input and the variations of vehicle parameters. Simulations showed the significant vehicle performance improvement from adaptation to road input; however, an adaptive Kalman filter is not very necessary.

The study in the paper is aimed to develop a yaw stability controller (YSC) by way of actively dynamic distribution of the longitudinal tire forces, which is considered to be one of the promising means of chassis control, so as to substantially improve the vehicle active safety even under some critical conditions. The control law, which ensures the vehicle follow the desired dynamic model via the feedforward control of side slip angle and the fuzzy control of the errors between the desired states and the corresponding practical ones, has been designed and implemented by using the hardware-in-the-loop (HiL) simulation technology under the Matlab/Simulink environment.

In partially automated and conditionally automated vehicles, a part of the work of human drivers is replaced by the system, and the main source of safety risks is no longer system failures, but non-failure risks caused by insufficient system function design. The absence of unreasonable risk due to hazards resulting from functional insufficiencies of the intended functionality or by reasonably foreseeable misuse by persons, is referred to as the Safety Of The Intended Functionality. Drivers have the responsibility to supervise the automated driving system. When they don't agree with the operation behavior of the system, they will interfere with the instructions. However, this may lead to potential risks.

An EV prototype, with all the wheels respectively driven by 4 inwheel motors, is developed, and undergoes a series of practical measurements and road tests. Based on the obtained vehicle parameters, a multi-body dynamics model is built by using SolidWorks and Adams/Car, and then validated by track test data. The virtual prototype is served as the control plant in simulation. An adaptive fractional order PID (A-FO-PID) controller is designed to enhance the handling and stability performance of the EV. Considering the model uncertainties, e.g. the variation in body mass distribution and the consequent change in yaw moment of inertial, a Parameter Self-Adjusting Differential Evolution (PSA-DE) algorithm is adopted for tuning the controller parameters, i.e. KP, KI, KD, λ and μ. As a modification of traditional DE algorithm, the so-called Variance of Population’s Fitness is utilized to evaluate the diversity of the population.

A new kind of integrated semi-track air-cushion pitch controller is proposed in this paper. The controller first compute the target working point based on a weighed function, which is the combination of optimal power consumption and pitch angle control demand. Then the sequential quadratic programming algorithm distributes the general target values to specific control values. The performance of the controller is verified through co-simulation between Matlab/Simulink and ADAMS/View. The simulation results show the effectiveness of the control algorithm and the correctness of the choice in physical configuration with two air cushions for vehicle body pitch control.