Evaluation of Slow Speed Off-Tracking of Steerable Axle Tractor Trailer Combinations 2019-26-0069
Steerable multi axle trailers are deployed for transportation due to their cost effectiveness and improved manoeuvrability then non-steered trailers. High speed manoeuvres of steerable axle trailer are considered dangerous for stability due to complex dynamic behaviour and researched for decades. Off-Tracking is an important parameter which influences the dynamic behaviour of steerable axle trailer at both low and high speed. Off-tracking is defined as maximum radial offset between path of the tractor’s front axle centre and trailer’s rearmost axle centre during a specific manoeuvre. Off-tracking, being a slow speed phenomenon becomes major concern for safe and accident free movement even at slow speeds.
A linear 3-DOF yaw plane model of steerable axle tractor trailer combination is developed using Lagrangian approach, which requires steering angles of truck’s front axle and all trailer axles to simulate the system. Trailer steering follows Command steering law hence, mathematical equations based on analytical Ackerman’s theory developed to evaluate ideal trailer steering angles. Further, actual steering angles by physical trailer steering mechanism are evaluated and optimised by MBD model prepared in ADAMS S/W. The dynamic system simulation is carried out to evaluate slow speed off-tracking for ideal trailer steering angles using mathematical equations in MATLAB as well as actual steering angles through Co-simulation approach.
Physical measurement of slow speed off-tracking carried out on 4 axle steerable semi trailer. A close correlation obtained with results of dynamic simulation with actual trailer steering angles, thus, proving the modelling and simulation approach.
The model so developed can be used for evaluation of slow speed off-tracking of different combinations of steerable axle trailers.
Vikram Saini, S P Singh, Sanjay Chaudhuri
VRDE Ahmednagar, Indian Institute of Technology - Delhi
Symposium on International Automotive Technology 2019