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Research Papers

A Method for Predicting Minimum-Time Capability of a Motorcycle on a Racing Circuit

[+] Author and Article Information
R. S. Sharp

Faculty of Engineering and Physical Sciences,
University of Surrey,
Guildford GU2 7XH, UK
e-mail: robinsharp37@talktalk.net

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received October 22, 2012; final manuscript received December 11, 2013; published online April 4, 2014. Assoc. Editor: Shankar Coimbatore Subramanian.

J. Dyn. Sys., Meas., Control 136(4), 041007 (Apr 04, 2014) (10 pages) Paper No: DS-12-1352; doi: 10.1115/1.4026324 History: Received October 22, 2012; Revised December 11, 2013

Prediction by simulation of the minimum-time lap of a flat and level racing circuit by a high-performance motorcycle is treated. A novel method is described. Constituents of the method comprise: (i) a high-fidelity mathematical model of the vehicle; (ii) a rider model with control of throttle/brake position, steering torque, and upper-body lean torque. The rider model uses linear quadratic optimal preview control with adaptation to variations in running conditions by gain scheduling; (iii) a circuit model; and (iv) a learning process through which the rider arrives at the best speed target. The constituents are discussed in turn. Then, systematic reduction of lap times for each of two circuits is demonstrated. Aspects of the performance of the motorcycle in very fast laps of the circuits are shown, providing evidence of the effectiveness of the method established.

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References

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Figures

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Fig. 1

Scaled motorcycle model showing the masses of the seven rigid bodies included, each with area in proportion to mass

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Fig. 2

Motorcycle model bodies showing tree structure and freedoms allowed

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Fig. 3

Rear wheel drive torque f1 * f2 as a function of rear wheel spin speed and normalized throttle opening

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Fig. 4

Transmission torque multiplier f3 as a function of motorcycle speed

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Fig. 5

Diagrammatic representation of a motorcycle tracking a specified path. xdem and ydem define the intended path points at time intervals of Ts while xtrim and ytrim are the discrete path points at these same intervals implied by the current trim state. Control inputs are sums of trim, state-perturbation-feedback and path-preview contributions. ns and np are the numbers of states and preview points, respectively.

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Fig. 6

Snapshot of motorcycle in a general motion state using local reference axes. The current trim defines points along a circular path while the intended path points are known through the preview. Differences constitute errors that are employed, together with the optimal preview gains, in the preview part of the control. Each complete control signal is made up of a trim-state part, a state-feedback part and a preview part; see also Fig. 5.

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Fig. 7

Catalunya circuit lap times for 18 successive completed laps

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Fig. 8

Silverstone circuit lap times for 51 successive completed laps

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Fig. 9

Catalunya circuit path and speed results for lap time 134.3 s. In the upper diagram, the crosses are 2 s apart in time.

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Fig. 10

Catalunya circuit roll angle and lateral acceleration results for lap time 134.3 s

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Fig. 11

Catalunya circuit control inputs for lap time 134.3 s

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Fig. 12

Silverstone circuit path results for lap time 153.36 s. The crosses are 2 s apart in time.

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Fig. 13

Silverstone circuit machine speed for lap time 153.36 s

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Fig. 14

Silverstone circuit roll angle and lateral acceleration results for lap time 153.36 s

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Fig. 15

Silverstone circuit control inputs for lap time 153.36 s

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