Davide Tavernini

Minimum time cornering: the effect of road surface and car transmission layout

This paper investigates the minimum time/limit handling car manoeuvring through nonlinear optimal control techniques. The resulting ‘optimal driver’ controls the car at its physical limits. The focus is on cornering: different road surfaces (dry and wet paved road, dirt and gravel off-road) and transmission layouts (rear-wheel-drive, front-wheel-drive and all-wheel-drive) are considered. Low-drift paved circuit-like manoeuvres and aggressive/high-drift even counter-steering rally like manoeuvres are found depending on terrain/layout combinations. The results shed a light on the optimality of limit handling techniques.

The Optimality of the Handbrake Cornering Technique

The paper investigates the optimality of the handbrake cornering, a strategy widespread among rally drivers. Nonlinear optimal control techniques are used to mimic real driver behavior. A proper yet simple cost function is devised to induce the virtual optimal driver to control the car at its physical limits while using the handbrake technique. The optimal solution is validated against experimental data by a professional rally driver performing the handbrake technique on a loose off-road surface. The effects of road surface, inertial properties, center of mass position, and friction coefficient are analyzed to highlight that the optimality of the maneuver does not depend on the particular vehicle data set used. It turns out that the handbrake maneuvering corresponds to the minimum time and minimum (lateral) space strategy on a tight hairpin corner. The results contribute to the understanding of one of the so-called aggressive driving techniques.

Modelling and estimation of friction brake torque for a brake by wire system

Recent advances in the automotive industry have incorporated the latest technology in vehicle electrification, with the aim to reduce fuel consumption, pollutants emissions, as well as enhance vehicle performance and safety. As a result, Electric Vehicles (EV) and Hybrid Electric Vehicles (HEV) have become the imminent automotive future, establishing important challenges in vehicle systems integration and control. In these vehicles, the regenerative braking is currently the major technique of energy recovery, providing accurate control on the brake torque applied. However regenerative brakes still need the support of conventional friction brakes, mainly due to the battery limitations. Consequently, the coordination of both braking strategies becomes critical for the safe actuation of braking related systems such as: ABS and ESP. Unfortunately, the torque blending between friction and regenerative brakes is a complicated task due to the different systems inputs; the regenerative brakes receive torque inputs, whilst the friction brakes work with pressure inputs. This paper proposes the friction brake torque estimation to simplify the torque blending, and improve the energy recovery and driving safety. The brake torque is estimated not only considering the pressure developed at the calipers, but also the brake disc temperature, and the wheel speed effect on the friction coefficient. The torque is obtained without installing additional sensors in the vehicle platform, considering that only wheel speed sensors are available. The estimation is performed using the extended version of the Kalman Filter. The results obtained are very satisfactory, and can improve the performance of the named systems in a safe way.

Optimization of the centre of mass position of a racing motorcycle in dry and wet track by means of the “Optimal Maneuver Method”

The “Optimal Maneuver Method” is an application of the optimal control theory that basically simulates an ideal driver and computes the actions and the trajectory to complete a maneuver in the minimum time. As an application of this method a 125 cc motorcycle and a real race circuit, in both dry and wet conditions, have been simulated, and the validation of the results by means of a comparison with real telemetry data is discussed. Afterwards two significant quantities, the height and the longitudinal position of the centre of mass of the vehicle, have been considered. The influence of variation on the minimum lap time, in the two track conditions discussed above, is presented.

On the optimality of handbrake cornering

The aim of this paper is to investigate the optimality of the handbrake cornering technique for a Front Wheel Drive vehicle. Nonlinear Optimal Control theory is used to formulate the problem of optimal cornering and to simulate manoeuvres used by race drivers. Handbrake cornering is optimal with an appropriate selection of the minimization cost. The optimal solution is validated against data collected during the execution of the technique by an expert race driver on a loose off-road surface. Further optimization results considering high adhesion road surface are obtained to show that the optimality of the technique is not affected by the road conditions.

Effect of handling characteristics on minimum time cornering with torque vectoring

ABSTRACT In this paper, the effect of both passive and actively-modified vehicle handling characteristics on minimum time manoeuvring for vehicles with 4-wheel torque vectoring (TV) capability is studied. First, a baseline optimal TV strategy is sought, independent of any causal control law. An optimal control problem (OCP) is initially formulated considering 4 independent wheel torque inputs, together with the steering angle rate, as the control variables. Using this formulation, the performance benefit using TV against an electric drive train with a fixed torque distribution, is demonstrated. The sensitivity of TV-controlled manoeuvre time to the passive understeer gradient of the vehicle is then studied. A second formulation of the OCP is introduced where a closed-loop TV controller is incorporated into the system dynamics of the OCP. This formulation allows the effect of actively modifying a vehicles handling characteristic via TV on its minimum time cornering performance of the vehicle to be assessed. In particular, the effect of the target understeer gradient as the key tuning parameter of the literature-standard steady-state linear single-track model yaw rate reference is analysed.

Light Electric Vehicle Enabled by Smart Systems Integration

For the first time in history, the majority of people live now in urban areas. What is more, in the next four decades, the number of people living in the world’s urban areas is expected to grow from 3.5 billion to 5.2 billion. At the same time, populations around the world are rapidly ageing. By 2050, the global population of people aged 60 years and over is expected to reach almost 2 billion, with the proportion of older people doubling between 2006 and 2050. This growth and ageing of the population will pose great challenges for urban mobility, which will be addressed within the SilverStream project. In particular, it will develop and demonstrate a radically new light and affordable Light Electric Vehicle concept for the ageing population in congested European cities with scarce parking space.

Feedback Brake Distribution Control for Minimum Pitch

ABSTRACT The distribution of brake forces between front and rear axles of a vehicle is typically specified such that the same level of brake force coefficient is imposed at both front and rear wheels. This condition is known as ‘ideal’ distribution and it is required to deliver the maximum vehicle deceleration and minimum braking distance. For subcritical braking conditions, the deceleration demand may be delivered by different distributions between front and rear braking forces. In this research we show how to obtain the optimal distribution which minimises the pitch angle of a vehicle and hence enhances driver subjective feel during braking. A vehicle model including suspension geometry features is adopted. The problem of the minimum pitch brake distribution for a varying deceleration level demand is solved by means of a model predictive control (MPC) technique. To address the problem of the undesirable pitch rebound caused by a full-stop of the vehicle, a second controller is designed and implemented independently from the braking distribution in use. An extended Kalman filter is designed for state estimation and implemented in a high fidelity environment together with the MPC strategy. The proposed solution is compared with the reference ‘ideal’ distribution as well as another previous feed-forward solution.