• International Journal of Automotive Technology
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• v.3 no.4
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• pp.165-170
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• 2002

For a vehicle Anti-lock Braking System (ABS), the control target is to maintain friction coefficients within maximum range to ensure minimum stopping distance and vehicle stability. But in order to achieve a directionally stable maneuver, tire side forces must be considered along with the braking friction. Focusing on combined braking and turning operation conditions, this paper presents a new control scheme for an ABS controller design, which calculates optimal target wheel slip ratio on-line based on vehicle dynamic states and prevailing road condition. A fuzzy logic approach is applied to maintain the optimal target slip ratio so that the best compromise between braking deceleration, stopping distance and direction stability performances can be obtained for the vehicle. The scheme is implemented using an 8-DOF nonlinear vehicle model and simulation tests were carried out in different conditions. The simulation results show that the proposed scheme is robust and effective. Compared with a fixed-slip ratio scheme, the stopping distance can be decreased with satisfactory directional control performance meanwhile.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1924-1934
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• 2011

This paper is concerned with the robustness evaluations of the guidance controller for a bimodal tram which is being developed by the Korea Railroad Research Institute (KRRI). The bimodal tram is an all-wheel steered multiple-articulated vehicle as a new kind of transportation vehicle. This vehicle has to be equipped with an automatic guidance system. In [1], such a controller has been recently proposed. However, since the performance is affected by weight change of the vehicle due to number of the passenger, model parameter uncertainties depending on the state of friction and the elasticity of the tire, and a typhoon, the controller designed must be examined with these conditions. As expected, because the vehicle dynamics is highly nonlinear, for the sake of investigating the robustness of the controller we compose two simulation ways based on the vehicle models which are implemented by the ADAMS and the MATLAB/LabVIEW toolboxes. Different uncertainties and a typhoon disturbance have been considered for the simulation conditions. Simulation results are shown.

• International Journal of Automotive Technology
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• v.4 no.4
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• pp.181-191
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• 2003

Since the nonlinearity and uncertainties which inherently exist in vehicle system need to be considered in active suspension control law design, this paper proposes a new control strategy for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a genetic algorithm (GA) based self-tuning PID controller and a fuzzy logic controller in two loops. In the control scheme, the PID controller is used to minimize vehicle body vertical acceleration, the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors. In order to improve the adaptability to the changes of plant parameters, based on the defined objectives, a genetic algorithm is introduced to tune the parameters of PID controller, the scaling factors, the gain values and the membership functions of fuzzy logic controller on-line. Taking a four degree-of-freedom nonlinear vehicle model as example, the proposed control scheme is applied and the simulations are carried out in different road disturbance input conditions. Simulation results show that the present control scheme is very effective in reducing peak values of vehicle body accelerations, especially within the most sensitive frequency range of human response, and in attenuating the excessive dynamic tire load to enhance road holding performance. The stability and adaptability are also showed even when the system is subject to severe road conditions, such as a pothole, an obstacle or a step input. Compared with conventional passive suspensions and the active vehicle suspension systems by using, e.g., linear fuzzy logic control, the combined PID and fuzzy control without parameters self-tuning, the new proposed control system with GA-based self-learning ability can improve vehicle ride comfort performance significantly and offer better system robustness.