In order to improve the crossing ability and the tractive performance of a vehicle operating on soft and wet terrain, travelling mechanism must be properly designed and the adaptation abihty to the changes of prevailing operation conditions is obviously needed. Based on the previous researches and developments of a wheeled air-cushion vehicle and a semi-walking wheeled air-cushion vehicle, a new hybrid vehicle that combines air-cushion technology with a travelling mechanism, i.e. a semitracked air-cushion (STAC) vehicle, has been developed. This paper proposed a new design principle for the semi-track air-cushion vehicle. A novel structure, i.e. a flexible joint mechanism as the prototype suspension system, is particularly described. Based on theoretical analysis, an optimization model is established for minimizing total power consumption. Experiments have been carried out to investigate the relationships among load distribution ratio, slip ratio, clearance height, vehicle speeds, resistances and power consumption in given terrain conditions. Experiment and simulation results showed that the developedvehicle can meet the demand of tractive and transport efficiency with its optimal state of using minimum total power consumption, and also satisfactory directional stability and ride comfort performances can be obtained.

For a vehicle Anti-lock Braking System (ABS), the control target isto maintain friction conefficients within maximun range to ensure minimum stopping distance and vehicle stability. But in order to achieve a directionally stable manetiver, tire side forces must ber considered along with the braking friciton. Focusinhg on combined braking and turning operation conditions. this paper presents a new control scheme for na ABS controlller design, which calculates optimal target wheel slip ratio on-line based on vehicle dynamic states and prevailing road condition. A fuzzy lgic approach is applied to maintain the optimal target slop ratio so that the best compromise between braking decelerationm, stopping distance and direction stability performaceas can be obtained for the vehicle. The scheme is implemented using an 8-DOF nonliear 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.

Since the nonlinearity which inherently exists in vehicle system need to be considered in active suspension control law design, a new control strategy is proposed for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a PID controller and a fuzzy logic controller in two loops. In this paper, the investigation is mainly focused on vehicle ride comfort performance and simulations in straight running operating condition are presented. The control goal is to minimize vehicle body vertical and pitch accelerations for passenger comfort. The control system consists of two parallel control loops. One loop, using PID control, is to minimize vehicle body vertical acceleration; and the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors. Based on a four degree-of-freedom nonlinear vehicle model, the algorithm is implemented and simulations are carried out in different road disturbance input conditions. Simulation results show that the control strategy is very effective in reducing peak values of vehicle body accelerations, especially within the most sensitive frequency range of human response and also with good stability even if the system is subject to a discrete event input, i.e., a sudden change of road conditions, such as a pothole, an obstacle or a step input. Compared with conventional passive suspensions and an active vehicle suspension by using a linear and fuzzy logic controls, the new designed control system can improve vehicle ride comfort performance significantly and offer better system robustness.

This paper presents a state obserer design for an adaptive vehicle suspension Based on simulations. two main issues are investigated, (a) the selection nf measurement signals in relation to estimation acuracy and sensing needs and (h) the effects of variations in both road inputs and vehicle parmeters on estimation accuracy Meanwhile, the system stabilities are also examined concerning the effects of using different combination of measurement states abd the system parameter variations in practical, possible ranges

Based on a half-vehicle model, an algorithm is proposed for a Kalman filter optimal active vehicle suspension system using the correlation betwecn front and rear wheel road inputs In this paper, two main issues were investigated, i.e. the estimation accuracy of the Kalman filter for state variables. and the potential improvements from wheelbase preview. Simulations showed good estimations from the state Observer. Howcver, if the wheelbase preview algorithm is incorporated, the cstimation accuracy for the additional states significantly decreases as vehicle speed and the corresponding measurement noises increase. Significant benefits from wheelbase preview were further proved, and the available perforrmance improvements of Ihe rear wheel station could be up to 35 per cent. Because of the feasibilily and effectiveness of the proposed algorithm, and no additional cost for measurements and sensing needs, wheelbase preview can be a promising algorithm for Kalman filter active suspension system designs.

Since the nonlinearity and uncertainties which inherently exist in vehicle system need to be considered in active suspension control law design, a new control strategy is proposed for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a genetic algorithm (CA) based self-tuning PID controller and a fuzzy logic controller in two loops. The PID controller is used to minimize vehicle body vertical acceleration and 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 achieve optimal vehicle performances and 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, gain values and the membership functionof fuzzy logic controller on-line. By a four degree-of-freedom nonlinear vehicle model, the proposed control scheme is implemented and simulations are carried out in different road disturbance input conditions. Simulation results show that the present control scheme is very effective in reducing peak valuesof vehicle body accelerations, especially within the most sensitive frequency range of human response, and attenuating the excessive tire deflection to enhance road holding performance. It also shows good stability and adaptability even if the system is subject to adverse roadconditions, such as a pothole, an obstacle or a step input. Compared with conventional passive suspensions and active vehicle suspension systems by using different control schemes, i.e., a linear and fuzzy logic control, the combined PID and fuzzy control without parameters self-tuning, the new proposed control system with CA-based self-learning ability in this paper can improve vehicle ride comfort performance significantly and offerbetter system robustness.

An optimal self-tuning control algorithm ispresented for vehicle suspension design. The controller, incorporating a weighting conroller, state observer and parameter estimator, is desined according to linear optimal control (LQG) theory. Based on the updated estimates of vehicle parameters and states, and the adapted weighting parameters, the LQG controller provides the optimal set of gains over different operating conditions. The feasibility and effectiveness of the proposed self-tuning system was investigated andproved by simulation studies.

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.

In order to reduce the development time and cost of vehicle control systems, the co-simulation approach has been paid great attention recently, which combines the advantages of different software packages and provide the means of rapid iteration of control algorithm and insight into its effects on vehicle performance in design stage. This paper presents the design process of a controller for bandwidth-limited active hydro-pneumatic suspension employed by an off-road vehicle based on the co-simulation technology. First, a detailed multi-body dynamic model of the vehicle is established by using ADAMS/View software package. Second, aiming at achieving high ride quality and handling performance so as to increase the vehicle traveling speed even on rough terrain surfaces, a combined PID and fuzzy controller is designed for the bandwidth-limited active suspension system and then worked out by means of S-functions provided by Matlab/Simulink. Third, the proposed control algorithm is integrated with the multi-body dynamic vehicle model by Control Interface and thus the cosimulation can be running repeatedly until a more practical controller is achieved. In the end, the proposed active suspension system is compared with conventional passive system. Simulation results show that the proposed active suspension system considerably improve both the ride and handling performance of the vehicle and therefore increase the maximum traveling speeds even on rough road surfaces.

In this paper, a non-linear, rigid-elastic coupling multibody system dynamic model is built for a city low-floor bus by using the integration of CAD/CAM/CAE techniques. Finite element analysis models of some flexible components are incorporated to the multi-body vehicle model. The non-linear properties of air spring and dampers are also included. Simulations are carried out in different operation conditions to investigate vehicle ride and handling performances. Based on the comparison of simulation results with field experiment results, the model is validated and the effectiveness of the modeling approach is proved.