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The tire cornering stiffness plays a vital role in the functionality of vehicle dynamics control systems, particularly when it comes to stability and path tracking controllers. This parameter relies on various external variables such as the tire/ambient temperature, tire wear condition, the road surface state, etc. Ensuring a reliable estimation of the cornering stiffness value is crucial for control systems. This ensures that these systems can accurately compute actuator requests in a wide range of driving conditions. In this paper, a novel estimation method is introduced that relies solely on standard vehicle sensor data, including data such as steering wheel angles, longitudinal acceleration, lateral acceleration, yaw rate, and vehicle speed, among others. Initially, the vehicle's handling characteristics are deduced by estimating the understeer gradient.

Anti-lock Braking System (ABS) is a critical safety component and its performance is crucial for every vehicle manufacturer. The tire plays an important role during an ABS braking maneuver as it is the component that connects the vehicle to the ground and is responsible for generating braking force. The steady-state and transient properties of the tire affect the operation of the vehicle's ABS system and consequently affects its performance/ operational efficiency. The main objective of this study is to investigate how tire design changes influence its interaction with the ABS and its eventual effect on stopping distance. This was conducted through an experimental study where tires were built with three levels of variation in carcass stiffness, tread stiffness and tread compound. Following this, ABS braking maneuvers were performed on two instrumented vehicles including a mid-tier sedan and a high-performance sports car.

Tread depth, inflation pressure, tire temperature, and road surface condition are among the most notable factors that have a noticeable effect on the tire force and moment characteristics. They can vary significantly during the operation of a tire and can effectively modify tire (and thus vehicle) performance. This study presents details of an adaptive magic formula (MF) tire model capable of coping with changes to the tire operating condition. More specifically, extensions have been made to the magic formula expressions for tire cornering stiffness and peak grip level, to account for variations in the tire inflation pressure, load, tread-depth and temperature. As a next step, the benefits of using an adaptive tire model for vehicle control system applications is demonstrated through simulation studies for enhanced vehicle control systems using an adaptive tire model in comparison to traditional control systems based on a non-adaptive tire model with fixed model parameters.

The effectiveness of active vehicle safety systems soars with the advances in on-board electronics that allows increasingly complex algorithms to be implemented. Numerous studies expose statistical results that underline the rate of reduction in the involvement of the vehicles equipped with such systems in road accidents. These facts clearly indicate how much the current systems have advanced. Nevertheless there are several areas of improvement for these systems, among which utilizing more information about tire-road states (e.g., tire forces, tire slip and slip-angle, surface friction) ranks very high due to the key role tires play in providing directional stability and control. This study introduces the use of an arriving technology, namely the smart tire technology, to estimate and utilize the aforementioned tire-road states along with an optimal tire force allocation scheme for improved vehicle stability.

In the case of modern day vehicle control systems employing a feedback control structure, a real-time estimate of the tire-road contact parameters is invaluable for enhancing the performance of the chassis control systems such as anti-lock braking systems (ABS) and electronic stability control (ESC) systems. However, at present, the commercially available tire monitoring systems are not equipped to sense and transmit high speed dynamic variables used for real-time active safety control systems. Consequently, under the circumstances of sudden changes to the road conditions, the driver's ability to maintain control of the vehicle maybe at risk. In many cases, this requires intervention from the chassis control systems onboard the vehicle. Although these systems perform well in a variety of situations, their performance can be improved if a real-time estimate of the tire-road friction coefficient is available.

Active safety systems have become an essential part of today's vehicles including SUVs and LTVs. Although they have advanced in many aspects, there are still many areas that they can be improved. Especially being able to obtain information about tire-vehicle states (e.g. tire slip-ratio, tire slip-angle, tire forces, tire-road friction coefficient), would be significant due to the key role tires play in providing directional stability and control. This paper first presents the implementation strategy for a dynamic tire slip-angle estimation methodology using a combination of a tire based sensor and an observer system. The observer utilizes two schemes, first of which employs a Sliding Mode Observer to obtain lateral and longitudinal tire forces. The second step then utilizes the force information and outputs the tire slip-angle using a Luenberger observer and linearized tire model equations.