Roll angle estimation in two-wheeled vehicles

Boniolo, Ivo; Tanelli, Mara; Savaresi, Sergio M.

doi:10.1109/cca.2008.4629599

Cited by 24 publications

(13 citation statements)

References 9 publications

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“…In 2008, precursor work was published about state estimation for motorcycles in [14]. In a first time, researchers have commonly addressed the estimation of the lean angle [15], [16], [17] and rapidly the aim was to estimate the whole dynamics states [18], [19] and more recently in [20] and [21]. These works dealing with P2WV dynamics estimation highlight the strong potential of these techniques.…”

Section: Motivation and Contextmentioning

confidence: 99%

Steering and Lateral Motorcycle Dynamics Estimation: Validation of Luenberger LPV Observer Approach

Damon

Ichalal

Arioui

2019

IEEE Trans. Intell. Veh.

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In this paper a validation of the Luenberger-like nonlinear observer, proposed in one of our recent work, is performed by means of a commercial motorcycle simulator. The previous paper has introduced the design of a nonlinear Luenberger observer to simultaneously estimate both the motorcycle lateral dynamics and the rider action. The vehicle lateral motion is described with a two-body linear model which takes into account the longitudinal speed variation as a time-varying parameter. Then, the Takagi-Sugeno approach combined to the Lyapunov theory, linear matrix inequalities tools and L 2-gain property are used to demonstrate the observer's convergence through an input-to-error stability. Finally, the effectiveness and the robustness of the observer are tested on three different realistic riding scenarios by means of the well-know multibody simulator BikeSim. Finally, the estimation performances are compared to previous works.

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Section: Motivation and Contextmentioning

confidence: 99%

Steering and Lateral Motorcycle Dynamics Estimation: Validation of Luenberger LPV Observer Approach

Damon

Ichalal

Arioui

2019

IEEE Trans. Intell. Veh.

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“…1 -which embeds a triaxial accelerations vector and two angular velocities, the roll-rate (ω x ) and yaw-rate (ω z ). This is the minimal sensor configuration already employed in recent motorcycles for estimating the lean angle [14] and which could be easily replicated using the modern, flexible, cost-effective, and easy to install telematic e-Boxes [15]. In Fig.…”

Section: Problem Statement and Experimental Setupmentioning

confidence: 99%

Analysis and development of an automatic eCall for motorcycles: a one-class cepstrum approach

Gelmini

Panzani

Savaresi

2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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The automatic dial of an emergency call -eCall -in response to a road accident is a feature that is gaining interest in the intelligent vehicle community. It indirectly increases the driving safety of road vehicles, but presents the technical challenge of developing an algorithm which triggers the emergency call only when needed, a non-trivial task for two-wheeled vehicles due to their complex dynamics. In the present work, we propose an eCall algorithm that detects these anomalies in the data time series, thanks to the cepstral analysis. The main advantage of the proposed approach is the direct focus on the data dynamics, solving the limits of approaches based on the analysis of the instantaneous value of some signals combination. The algorithm is calibrated and tested against real driving data of ten different drivers, including seven real crash events, and performance are compared with known methods.

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“…Indeed, the first observer estimating the roll angle of a motorcycle dates back to 2004 [11]. Several studies have been proposed for estimating the lateral dynamics; however, the steering dynamics has often been neglected: based on frequency separation filtering [12], [13], Kalman filtering [14], [15], PMI observer [16] or TS observer [17]. These techniques are developed under strict assumptions (neglect of the steering dynamics, neglect of tire-road contact, etc.)…”

Section: Introductionmentioning

confidence: 99%

Unknown-input observer design for motorcycle lateral dynamics: TS approach

Dabladji

Ichalal

Arioui

et al. 2016

Control Engineering Practice

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In this paper, a nonlinear observer is designed in order to estimate the lateral dynamics of motorcycles. A nonlinear model of motorcycle's lateral dynamics is considered and is transformed in a Takagi-Sugeno (TS) exact form. An unknown input (UI) nonlinear observer is then designed in order to reconstruct the state variables whatever the forward velocity variations. The observer convergence study is based on the Lyapunov theory. The boundedness of the state estimation error is guaranteed thanks to the Input to State Stability (ISS) property. The observer has been tested on a nonlinear multibody model.

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Roll angle estimation in two-wheeled vehicles

Cited by 24 publications

References 9 publications

Steering and Lateral Motorcycle Dynamics Estimation: Validation of Luenberger LPV Observer Approach

Steering and Lateral Motorcycle Dynamics Estimation: Validation of Luenberger LPV Observer Approach

Analysis and development of an automatic eCall for motorcycles: a one-class cepstrum approach

Unknown-input observer design for motorcycle lateral dynamics: TS approach

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