2021
DOI: 10.1080/00423114.2021.1910718
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Minimum-lap-time optimisation and simulation

Abstract: The paper begins with a survey of advances in state-of-the-art minimum-time simulation for road vehicles. The techniques covered include both quasi-steady-state and transient vehicle models, which are combined with trajectories that are either pre-assigned, or free to be optimized. The fundamentals of nonlinear optimal control are summarized. These fundamentals are the basis of most of the vehicular optimal control methodologies and solution procedures reported in the literature. The key features of three-dime… Show more

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Cited by 40 publications
(32 citation statements)
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References 104 publications
(192 reference statements)
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“…In other words, we seek (s-dependent) Euler angles and polynomial coefficients a i ðsÞ in ( 7) that minimise the distance between the survey data and the track model. The method proposed builds on the methods described in [7,13,15]. The optimal-control problem (OCP) takes the standard form…”
Section: Road Reconstructionmentioning
confidence: 99%
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“…In other words, we seek (s-dependent) Euler angles and polynomial coefficients a i ðsÞ in ( 7) that minimise the distance between the survey data and the track model. The method proposed builds on the methods described in [7,13,15]. The optimal-control problem (OCP) takes the standard form…”
Section: Road Reconstructionmentioning
confidence: 99%
“…where ½X x ; X y ; X z T is given by (15). These equations are identical to those of the standard three-dimensional road model, once the road curvatures of the centre line are replaced by those at P; see equation (7.106) in [10].…”
Section: Vehicle Positioning and Kinematicsmentioning
confidence: 99%
“…Equation ( 4) constraints n and χ, while the speed along the centreline ṡ is the link between the space-and the time-domain formulations, since dx/dt = ṡdx/ds. Indeed, it is common to solve minimum-time problems in the space domain instead of the time domain [1].…”
Section: Vehicle Positioningmentioning
confidence: 99%
“…(cos µ cos χ + sin µ sin φ sin χ) cos θ − cos φ sin χ sin θ cos φ sin χ cos θ + (cos µ cos χ + sin µ sin φ sin χ) sin θ cos µ sin φ sin χ − sin µ cos χ   , (20) where R(θ, µ, φ) is from (1). The projection on the ground plane x-y is obtained from the norm of the first two components of ( 20)…”
Section: Racing-line Reconstructionmentioning
confidence: 99%
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