Optimal State Estimation

Racecar drivers have the ability to operate a vehicle at its friction limit without losing control. If autonomous vehicles or driver assistance systems had similar capabilities, many fatal accidents could be avoided. To advance this goal, an autonomous racing controller is designed to gain insights into vehicle control at the friction limits. A bicycle model and a ‘ g-g ’ diagram are used to mimic racecar drivers’ internal vehicle model. Lanekeeping steering feedback and wheel slip feedback controllers are used to imitate drivers making steering and throttle corrections according to the vehicle responses. Experimental results on a low friction surface demonstrate that the controller can robustly track a path while operating at the limits of tyre adhesion and provide insights for the future development of vehicle safety systems.

/pdf/autonomous-vehicle-control-at-the-limits-of-handling-bfbbj266cq.pdf

Autonomous Vehicle Control at the Limits of Handling

Race Car Vehicle Dynamics

Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developments in the estimation of vehicle dynamic states. The definitions used in vehicle dynamic state estimation are first introduced, and alternative estimation structures are presented. Then, the sensor configuration schemes used to estimate vehicle velocity, sideslip angle, yaw rate and roll angle are presented. The vehicle models used for vehicle dynamic state estimation are further summarized, and representative estimation approaches are discussed. Future concerns and perspectives for vehicle dynamic state estimation are also discussed.

Vehicle dynamic state estimation: state of the art schemes and perspectives

A formal method for the evaluation of the minimum time vehicle manoeuvre is described The problem is treated as one of Optimal Control and is solved using a direct transcription method The resulting Non Linear Programming problem is solved using a Sequential Quadratic Programming (SQP) algorithm for constrained minimisation of a multivariable function The optimisation program is used to investigate the effect of the yaw moment of inertia on vehicle performance in a double lane change manoeuvre The method is shown to have excellent capabilities to predict the vehicle maximum performance in transient conditions and to perform sensitivity analysis The influence of yaw inertia on the minimum manoeuvre time is found to be surprisingly small The extension of the method to larger problems, eg, lap time simulation, is also discussed

Minimum Time Manoeuvring: The Significance of Yaw Inertia

Typical active safety systems that control the dynamics of passenger cars rely on the real-time monitoring of the vehicle sideslip angle (VSA), together with other signals such as the wheel angular velocities, steering angle, lateral acceleration, and the rate of rotation about the vertical axis, which is known as the yaw rate. The VSA (also known as the attitude or “drifting” angle) is defined as the angle between the vehicle’s longitudinal axis and the direction of travel, taking the centre of gravity as a reference. It is basically a measure of the misalignment between vehicle orientation and trajectory; therefore, it is a vital piece of information enabling directional stability assessment, such as in transience following emergency manoeuvres, for instance. As explained in the introduction, the VSA is not measured directly for impracticality, and it is estimated on the basis of available measurements such as wheel velocities, linear and angular accelerations, etc. This work is intended to provide a comprehensive literature review on the VSA estimation problem. Two main estimation methods have been categorised, i.e., observer-based and neural network-based, focussing on the most effective and innovative approaches. As the first method normally relies on a vehicle model, a review of the vehicle models has been included. The advantages and limitations of each technique have been highlighted and discussed.

https://www.mdpi.com/2076-3417/8/3/355/pdf

On the vehicle sideslip angle estimation: a literature review of methods, models and innovations

It is well known that vehicle slip angle is one of the most difficult parameters to measure on a vehicle during testing or racing activities. Moreover, the appropriate sensor is very expensive and it is often difficult to fit to a car, especially on race cars. We propose here a strategy to eliminate the need for this sensor by using a mathematical tool which gives a good estimation of the vehicle slip angle. A single-track car model, coupled with an extended Kalman filter, was used in order to achieve the result. Moreover, a tuning procedure is proposed that takes into consideration both nonlinear and saturation characteristics typical of vehicle lateral dynamics. The effectiveness of the proposed algorithm has been proven by both simulation results and real-world data.

Development and validation of a Kalman filter-based model for vehicle slip angle estimation

The top Formula 1 and Indycar teams make large use of computer simulation to improve the performance of their cars and make the set-up process quicker on the circuit. The paper aims to present a lap time simulation software dedicated to racing cars. It is based on the background of vehicle dynamics research developed at the University of Brescia, Italy (see [1]). It should be stated that racecar dynamics is strongly nonlinear due to the fact that tyres are always very near the limit of adhesion. Moreover this makes the effect of lateral load transfer fundamental for the general balance of the car. Therefore Pacejka's Magic Formula has been used for lateral force/slip while longitudinal force computation is based on the assumption of a maximum longitudinal coefficient of friction μ. This is not only for simplicity but it is also due to lack of available data. The combined case is then based on the so-called "traction circle". Lateral and longitudinal load transfer and downforce as well as their effects on tyre load are taken into account. The vehicle model is capable of following a trajectory acquired with the on-board instrumentation. Also, the use of genetic algorithms enables the program to find the optimum cornering line for any given track. Some results are shown and compared with real world data.

A Tool for Lap Time Simulation

Student competitions can play an important role in education: they promote interest and engagement of the students, as well as of the teachers. In the case of engineering, one of the most challengi...

https://journals.sagepub.com/doi/pdf/10.1177/0306419017749580

Experiential learning in engineering education: The role of student design competitions and a case study:

In this work, optimal control theory is applied to minimum lap time simulation of a GP2 car, using a multibody car model with enhanced load transfer dynamics. The mathematical multibody model is fo...

/pdf/minimum-time-optimal-control-simulation-of-a-gp2-race-car-55izuc05zi.pdf

Marco Gadola

Papers

On the vehicle sideslip angle estimation: a literature review of methods, models and innovations

Development and validation of a Kalman filter-based model for vehicle slip angle estimation

A Tool for Lap Time Simulation

Experiential learning in engineering education: The role of student design competitions and a case study:

Minimum time optimal control simulation of a GP2 race car