A study on lateral speed estimation methods

Abstract

The estimation of vehicle lateral speed, a critical variable for vehicle stability control, four-wheel-steering and other advanced dynamic control systems, is studied in this paper. We presented three different approaches, one each from three categories: transfer function approach, state-space approach, and kinematics approach. The first two methods rely on a vehicle dynamic (bicycle) model, and the last approach is based on the kinematics relationship of measured signals. The basic formulation of all three methods assumed that the road bank angle is negligible, and thus needs to be enhanced by a road bank angle estimation algorithm to work satisfactorily when the road bank is significant. The performance of these three (enhanced) methods are investigated using simulation and experimental data. For the experimental verification, we present four cases: nominal (high friction, flat road), banked road, low-friction, and low-friction-near-spin. Weakness of the three estimation algorithms is discussed.

Adaptive integrated vehicle control using active front steering and rear torque vectoring

“…Indeed, this is difficult to estimate. Various observers for the lateral velocity v y have been proposed in the literature (see Ungoren et al (2006), among the others), and can be considered for the implementation of the controller.…”

Sideslip angle estimator based on ANFIS for vehicle handling and stability

“…In addition, the sideslip angle can be directly measured via optical or GPS sensors [5,6,7]. However, the drawbacks of measuring the yaw rate and the sideslip angle are accuracy, reliability and cost [8]. Sideslip angle cannot be directly measured using standard sensors, therefore, it must be estimated by means of an observer [9,10,11].…”

“…The modeling of sideslip angle is complex due to the non-linear dynamics of the vehicle. Some authors employ physical models for the estimation of sideslip angle [12,13,14,15]. Most mentioned methods are based on the bicycle dynamic model or its variations.…”

Nonlinear Observer for Vehicle Velocity with Friction and Road Bank Angle Adaptation - Validation and Comparison with an Extended Kalman Filter

“…Earlier work on observers for estimation of lateral velocity is mainly based on linear or quasi-linear techniques, for example [4,22,20,3]. A nonlinear observer linearizing the observer error dynamics is proposed in [13,14].…”