Fredrik Bruzelius

Longitudinal Velocity and Road Slope Estimation in Hybrid Electric Vehicles Employing Early Detection of Excessive Wheel Slip

Vehicle speed is one of the important quantities in vehicle dynamics control. Estimation of the slope angle is in turn a necessity for correct dead reckoning from vehicle acceleration. In the present work, estimation of vehicle speed is applied to a hybrid vehicle with an electric motor on the rear axle and a combustion engine on the front axle. The wheel torque information, provided by electric motor, is used to early detect excessive wheel slip and improve the accuracy of the estimate. A best-wheel selection approach is applied as the observation variable of a Kalman filter which reduces the influence of slipping wheels as well as reducing the computational effort. The performance of the proposed algorithm is illustrated on a test data recorded at a winter test ground with excellent results, even for extreme conditions such as when all four wheels are spinning.

LPV-based gain scheduling technique applied to a turbo fan engine model

Linear parameter varying (LPV) system based gain scheduling design is applied to a nonlinear jet engine model. A major shortcoming of LPV based gain scheduling techniques is the transformation step of the nonlinear system into an LPV system. It is crucial to have an accurate LPV model to design a controller meeting the performance specifications. Here, the nonlinear model is transformed into an LPV system using velocity based linearization. The derived state feedback controller has, under the assumption of a correct transformation, a guaranteed L/sub 2/ performance for the considered operating range. The performance of the controller is illustrated by simulations of the closed loop system.

Experimental Validation of the Brush Tire Model

The paper contains an experimental validation of the physically based brush-tire model toward the tire behavior in a number of different realistic conditions. Results of measurements performed with summer, winter, and studded tires on different road foundations such as wet and dry asphalt, basalt, snow, and ice are presented. The purpose behind the validation is to study the possibilities of using the brush model to estimate the friction coefficient from measurements or estimates of the longitudinal tire forces and tire slip. The sensitivity of the included tire parameters toward various factors that may change during normal run of the vehicle is also investigated.

Validation of a basic combined-slip tyre model for use in friction estimation applications

Tyre modelling is an important part of understanding and estimating the tyre–road friction. In this paper a basic steady-state tyre model for the combined-slip case is derived. The model is intended to be used in friction estimations applications, where the model complexity is of high priority. The model, described using only two parameters, is validated with measured data from various conditions and tyre types using mobile measurement equipment. The performance from the measurements suggests that only two parameters are sufficient for the combined-slip case.

A basic vehicle dynamics model for driving simulators

Driving simulators are a useful research tool in studies of vehicle and transport-related human machine interface. A vital part of the driving simulator is the vehicle dynamics model. In the present paper, such a model is developed. The model implements basic first order phenomena, but is yet complete in the terms of modelled parts of the vehicle. A major challenge is the trade-off between simplicity and accuracy imposed by the capabilities of the driving simulators motion platform. The modelling language Modelica was used for readability reasons. The model has been validated toward both measurements of a real car and subjectively in a driving simulator. It is shown that the model is well capable of fulfilling the imposed requirements, despite its simplicity. The model is open and available upon request.

Gain scheduling via affine linear parameter-varying systems and /spl Hscr//sub /spl infin// synthesis

An alternative method for gain scheduling is considered, based on so called affine linear parameter varying systems (LPV) and an /spl Hscr//sub /spl infin//-like method. It is shown that the necessary constraints for existence of such a controller can be reduced. This decreases the computational burden, in the process of finding a controller. The method is illustrated by application to a 3-state Moore-Greitzer compressor model. The nonlinear model is rewritten as a so called quasi-LPV system which the control synthesis is based on, and the derived controller is simulated with the nonlinear model.

Design of tyre force excitation for tyre–road friction estimation

ABSTRACT Knowledge of the current tyre–road friction coefficient is essential for future autonomous vehicles. The environmental conditions, and the tyre–road friction in particular, determine both the braking distance and the maximum cornering velocity and thus set the boundaries for the vehicle. Tyre–road friction is difficult to estimate during normal driving due to low levels of tyre force excitation. This problem can be solved by using active tyre force excitation. A torque is added to one or several wheels in the purpose of estimating the tyre–road friction coefficient. Active tyre force excitation provides the opportunity to design the tyre force excitation freely. This study investigates how the tyre force should be applied to minimise the error of the tyre–road friction estimate. The performance of different excitation strategies was found to be dependent on both tyre model choice and noise level. Furthermore, the advantage with using tyre models with more parameters decreased when noise was added to the force and slip ratio.

A simple real–time aerodynamic model for vehicles in overtaking situations

Aerodynamic forces and moments play an important role in, e.g., overtaking situations, and affect the trajectory of the involved vehicles. One method of studying these effects and how the driver responds is via driving simulator studies. However, models that describe aerodynamic forces and moments are typically computationally complex and not suited for real time execution in driving simulators. The present work presents a simplified real time model of the moments and forces acting in an overtaking situation due to aerodynamic pressure imbalances. The model is compared with experimentally validated Navier-Stokes solutions. Despite the models simplicity, implemented as finite impulse response filters, it manages to capture the main features of the forces and moments. The approach used to derive the model is fairly general and might be used in similar applications where the computational burden is a key issue.

Strict LMI conditions for stability and stabilization of discrete-time descriptor systems

For linear discrete-time descriptor systems, we consider stability and stabilization conditions using matrix inequality approach. We present a new strict linear matrix inequality (LMI) condition which is necessary and sufficient for stability of unforced descriptor systems. Then, we use the condition to consider stabilization problem by descriptor variable feedback and static output feedback. By introducing a new matrix variable with certain structure, we establish sufficient conditions in form of strict LMI for stabilizing controller design.

Effects of Visual Latency on Vehicle Driving Behavior

Using mixed reality in vehicles provides a potential alternative to using driving simulators when studying driver-vehicle interaction. However, virtual reality systems introduce latency in the visual system that may alter driving behavior, which, in turn, results in questionable validity. Previous studies have mainly focused on visual latency as a separate phenomenon. In this work, latency is studied from a task-dependent viewpoint to investigate how participants’ driving behavior changed with increased latency. In this study, the investigation was performed through experiments in which regular drivers were subjected to different levels of visual latency while performing a simple slalom driving task. The drivers’ performances were recorded and evaluated in both lateral and longitudinal directions along with self-assessment questionnaires regarding task performance and difficulty. All participants managed to complete the driving tasks successfully, even under high latency conditions, but were clearly affected by the increased visual latency. The results suggest that drivers compensate for longer latencies by steering more and increasing the safety margins but without reducing their speed.