Estimation of vehicle lateral tire-road forces: A comparison between extended and unscented Kalman filtering

Abstract

Abstract-Extensive research has shown that most of road accidents occur as a result of driver errors. A close examination of accident data reveals that losing the vehicle control is responsible for a huge proportion of car accidents. Preventing such kind of accidents using vehicle control systems, requires certain input data concerning vehicle dynamic parameters and vehicle road interaction. Unfortunately, some parameters like tire-road forces and sideslip angle, which have a major impact on vehicle dynamics, are difficult to measure in a car. Therefore, this data must be estimated. Due to the system nonlinearities and unmodeled dynamics, two observers derived from extended and unscented Kalman filtering techniques are proposed and compared. The estimation process method is based on the dynamic response of a vehicle instrumented with cheap, easily-available standard sensors. Performances are tested and compared to real experimental data acquired using the INRETS-MA Laboratory car. Experimental results demonstrate the ability of this approach to provide accurate estimations, and show its practical potential as a low-cost solution for calculating lateral-tire forces and sideslip angle.

Survey on Modelling and Techniques for Friction Estimation in Automotive Brakes

“…Herein, a new approach based on the Kalman theory is featured, which aims at estimating the BLCF by drawing upon the observation of the wheel torque. Referring to the state of the art, research effort in the last two decades has been mainly conducted in the fields of observation of the tire-road friction coefficient [68][69][70] and direct observation of the tire forces [71,72]. The bulk of the literature assumes the wheel torque as an input of the state equations; instead, for the matter in hand, it constitutes one of the states to observe in order to estimate BLCF [73].…”

Tire force estimation for a passenger vehicle with the Unscented Kalman Filter

“…Inputs to the model were the steering angle signal, all four angular wheel velocities as well as acceleration signals and yaw rate. DOUMIATI developed a method for the estimation of individual lateral and per-axle longitudinal tire forces neglecting rear longitudinal forces [10]. In a first block normal tire forces were estimated with suspension deflection measurements and acceleration signals.…”

Tire/road friction coefficient estimation applied to road safety

“…Two observation techniques were used in this process, the Extended Kalman Filter (EKF) and the UKF (Unscented Kalman Filter). More details can be found in our previous work [7].…”

“…In our previous studies, we have developed observers that can estimate the tire-road forces in real time during the vehicle motion [7]. We will therefore use these results in estimating the maximum friction.…”

“…The estimation process consists of two blocks, and its role is to estimate side slip angle, normal and lateral forces at each tire/road contact point, which provides the input of the process of estimating the maximum friction described in Section IV. Modeling vehicle dynamics (roll model, 4-wheel dynamic model) is presented in detail in [7].…”