Lateral-Directional Motorcycle Dynamics and Rider Control

Weir, David H.; Zellner, John W.

doi:10.4271/780304

Cited by 45 publications

(20 citation statements)

References 8 publications

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“…Rice [12] performed a number of tests on motorcycles in order to obtain performance characteristics for handling and safety. Weir and Zellner [21] tested transient behaviour of motorcycles in some standard manoeuvres and compared some results with their model. Ruijs and Pacejka [16] built a rider robot to validate their computer model eliminating disturbances originating from the human rider.…”

Section: Introductionmentioning

confidence: 99%

Experimental validation of a model of an uncontrolled bicycle

2007

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In this paper, an experimental validation of some modelling aspects of an uncontrolled bicycle is presented. In numerical models, many physical aspects of the real bicycle are considered negligible, such as the flexibility of the frame and wheels, play in the bearings, and precise tire characteristics. The admissibility of these assumptions has been checked by comparing experimental results with numerical simulation results.The numerical simulations were performed on a three-degree-of-freedom benchmarked bicycle model. For the validation we considered the linearized equations of motion for small perturbations of the upright steady forward motion. The most dubious assumption that was validated in this model was the replacement of the tires by knife-edge wheels rolling without slipping (non-holonomic constraints).The experimental system consisted of an instrumented bicycle without rider. Sensors were present for measuring the roll rate, yaw rate, steering angle, and rear wheel rotation. Measurements were recorded for the case in which the bicycle coasted freely on a level surface. From these measured data, eigenvalues were extracted by means of curve fitting. These eigenvalues were then compared with the results from the linearized equations of motion of the model. As a result, the model appeared to be fairly accurate for the low-speed low-frequency behaviour.

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Section: Introductionmentioning

confidence: 99%

Experimental validation of a model of an uncontrolled bicycle

2007

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“…His linearization was found to be correct except for typographical errors. They agree with Döhring [4], with Neȋmark and Fufaev [12] (after correcting errors due to an incorrect potential energy), with Sharp [22] (with a minor algebraic correction for the case of knife-edge wheels), with the Ph.D. thesis by Weir [26], with Weir and Zellner [27] (after correcting a sign error), and with the equations as derived by Hand [5], and simplified by Papadopoulos [13]. Moreover, Hand's work also gives a detailed literature review.…”

Section: Introductionmentioning

confidence: 99%

Benchmark results on the linearized equations of motion of an uncontrolled bicycle

2005

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In this paper we present the linearized equations of motion for a bicycle as a benchmark. The results obtained by pencil-and-paper and two programs are compared. The bicycle model we consider here consists of four rigid bodies, viz. a rear frame, a front frame being the front fork and handlebar assembly, a rear wheel and a front wheel, which are connected by revolute joints. The contact between the knife-edge wheels and the flat level surface is modelled by holonomic constraints in the normal direction and by non-holonomic constraints in the longitudinal and lateral direction. The rider is rigidly attached to the rear frame with hands free from the handlebar. This system has three degrees of freedom, the roll, the steer, and the forward speed. For the benchmark we consider the linearized equations for small perturbations of the upright steady forward motion. The entries of the matrices of these equations form the basis for comparison. Three different kinds of methods to obtain the results are compared: pencil-and-paper, the numeric multibody dynamics program SPACAR, and the symbolic software system AutoSim. Because the results of the three methods are the same within the machine round-off error, we assume that the results are correct and can be used as a bicycle dynamics benchmark.

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“…The role of the rider as an active controller is studied in some detail in [74], where it is recognized that inadvertent rider motions can have a significant influence on the vehicle's behavior. The focus of [74] is to treat the rider as a feedback compensator that maps the vehicle's roll angle errors into a steering torque, where the controller's characteristics are chosen to mimic those of the rider's neuromuscular system.…”

Section: Rider Modelingmentioning

confidence: 99%

“…The focus of [74] is to treat the rider as a feedback compensator that maps the vehicle's roll angle errors into a steering torque, where the controller's characteristics are chosen to mimic those of the rider's neuromuscular system. The rider is modeled (roughly) as being able to control his upper body roll angle as well as the steering torque; the steering torque influence is found to be dominant.…”

Section: Rider Modelingmentioning

confidence: 99%