Sensitivity of rearward amplication control of a truck/full trailer to tyre cornering stiffness variations

Abstract

Highway safety and vehicle performance are two important considerations in the design of a heavy vehicle combination. In this paper a performance measure called the 'rearward amplication ratio' ( RWA) is used as a control criterion in the design of a vehicle-handling controller. This approach is diVerent to conventional control techniques. The RWA is de ned as the ratio of the peak lateral acceleration at the rearmost trailer's centre of gravity (CG ) to that of the lead unit during a lane-change manoeuvre. The vehicle under consideration is a six-axle truck/full trailer, which usually exhibits a high level of RWA leading to roll-over during obstacle avoidance manoeuvres.In this study, several control strategies are examined, namely active yaw control at the truck CG, active yaw control at the dolly CG and active yaw control at the trailer CG. These could be employed individually or in combination. The eVect of an active control torque applied to various vehicle units is examined by using an optimal linear quadratic regulator approach combined with a simpli ed four degrees-of-freedom linear vehicle model. The controller performance index parameters are determined for the vehicle based on acceptable RWA target values. The sensitivity of the controller to tyre cornering stiVness variation is further evaluated.Simulation results indicate that the RWA can be reduced without signi cant change of the uncontrolled vehicle trajectory when active yaw torque is applied to the dolly. The controller can be more eVective in improving the dynamic performance and roll stability of this type of commercial vehicle, if applied to the lead unit (truck) or to the last unit (trailer). However, the path of the vehicle will be strongly in uenced and driving diYculties can be experienced. For active yaw control at the dolly CG, the optimal controller is found to be most sensitive to the dolly's tyres' cornering stiVness variations and least sensitive to steering axle from the RWA point of view. It is also found that the controller is most sensitive to steering axle parameter variations for path following.

A closed-loop dynamic simulation-based design method for articulated heavy vehicles with active trailer steering systems

“…On the other hand, AHVs exhibit unstable motion modes at high speeds, including jackknifing, trailer swing, and roll-over [7]. The unstable modes may lead to fatal accidents.…”

“…The maximum RWA ratio accepted by the PBS is tied to the static roll-over threshold. Roll stability is highly dependent on the RWA ratio [7]. The yaw damping coefficient has significant effects on the rearmost trailer swing and the articulation angles between adjacent units of an AHV.…”

“…It is reported that the location of steerable axles and the types of steering mechanism have significant effects on the dynamic stability of a tractor/trailer system [9]. The RWA ratio has been used as a control criterion in the design of active yaw controllers for a tractor/full-trailer combination [7]. Compared with the baseline vehicle, the one with the active trailer yaw controller can reduce the RWA ratio without significant change of the baseline vehicle's PFOT at low speeds.…”

“…The researchers intended to identify the correlation between the RWA ratio and the PFOT value in order to reduce the latter through minimising the former. Another solution accepted to date is to use a passive and an ATS system alternatively [1,3,7]. At low speeds, the passive steering systems are employed in order to effectively decrease PFOT values.…”

“…Hence, the linear vehicle model was adopted in the research. (2) In order to investigate the variations of RWA ratio of AHVs and derive lateral motion control algorithms, linear yaw plane models are usually used [2,3,7,9,10,13]. (3) Nonlinear three-dimensional articulated vehicle models considering rolling motion have been used to achieve accurate numerical results and validate the control algorithms derived from simplified linear models [17,18].…”