Investigation on the Model-Based Control Performance in Vehicle Safety Critical Scenarios with Varying Tyre Limits

Abstract

In recent years the increasing needs of reducing the costs of car development expressed by the automotive market have determined a rapid development of virtual driver prototyping tools that aims at reproducing vehicle behaviors. Nevertheless, these advanced tools are still not designed to exploit the entire vehicle dynamics potential, preferring to assure the minimum requirements in the worst possible operating conditions instead. Furthermore, their calibration is typically performed in a pre-defined strict range of operating conditions, established by specific regulations or OEM routines. For this reason, their performance can considerably decrease in particularly crucial safetycritical situations, where the environmental conditions (rain, snow, ice), the road singularities (oil stains, puddles, holes), and the tyre thermal and ageing phenomena can deeply affect the adherence potential. The objective of the work is to investigate the possibility of the physical model-based control to take into account the variations in terms of the dynamic behavior of the systems and of the boundary conditions. Different scenarios with specific tyre thermal and wear conditions have been tested on diverse road surfaces validating the designed model predictive control algorithm in a hardware-in-the-loop real-time environment and demonstrating the augmented reliability of an advanced virtual driver aware of available information concerning the tyre dynamic limits. The multidisciplinary proposal will provide a paradigm shift in the development of strategies and a solid breakthrough towards enhanced development of the driving automatization systems, unleashing the potential of physical modeling to the next level of vehicle control, able to exploit and to take into account the multi-physical tyre variations.

Keywords: double lane change; model-based control; safety optimization; tyre thermodynamics; tyre wear; vehicle dynamic potential; vehicle safety; weather influence.

Figure 1

Tyre behavior variations. (a) Compound temperature influence on the characteristic interaction shape. (b) Wear effect on available grip.

Figure 2

MF-based standard and evo tyre models compared with the experimental points in three thermal ranges: under-heating condition (a), optimal temperature (b), over-heating condition (c), (camber angle = $-2deg$|vertical load = $3000N$).

Figure 3

Comparison between outdoor acquisitions and simulation output. (a) Steering angle vs. lateral acceleration diagram. (b) Sideslip angle vs lateral acceleration diagram.

Figure 4

Example of lateral maneuver’s input reproduction. (a) Experimental and simulation steering angle comparison. (b) Slow-ramp-steer trajectory in virtual environment.

Figure 5

New tyre in optimal thermal condition in contact with different road surfaces. (a) Lateral interaction characteristics. (b) Adherence ellipse.

Figure 6

New and worn tyres in diverse thermal conditions in contact with the dry road. (a) Lateral interaction characteristics. (b) Adherence ellipse.

Figure 7

SRS maneuver on different road surfaces. (a) Vehicle understeer characteristics. (b) Maximum velocity achieved.

Figure 8

Internal vehicle model for control.

Figure 9

Co-simulaton platform.

Figure 10

(a) Vehicle trajectory performed in the DLC maneuvers in a different road surface (dry in black, wet in red, snow in blue, and icy in light blue), but with the same tyre (new tyre in optimal range temperature) for a NMPC tuned to better perform the maneuver in all road surface, tyre, and temperature condition. (b) Vehicle velocity.

Figure 11

(a) $\beta$ angle. (b) Yaw angle. (c) Time.

Figure 12

(a) Vehicle trajectory. (b) Vehicle velocity.

Figure 13

(a) Side slip angle. (b) Yaw angle. (c) Time.

Figure 14

(a) Vehicle trajectory performed in the DLC maneuvers in a dry road, with different tyre condition (New tyre (continuous lines) and worn tyre (dashed lines) in optimal (black), cold (blue), and overheated (red) temperature range. (b) Vehicle velocity.

Figure 15

(a) Side slip angle. (b) Yaw angle. (c) Time.

Figure 16

Slip ratio achieved for the four tyres.

Figure 17

(a) Vehicle trajectory performed in the DLC maneuvers in a dry, wet, and snow road, with new tyre in optimal range temperature. (b) Vehicle velocity.

Figure 18

(a) Side slip angle. (b) Yaw angle. (c) Time.

Figure 19

(a) Vehicle trajectory performed in the DLC maneuvers in conservative vs global configuration. (b) Vehicle velocities.

Figure 20

(a) Side slip angles. (b) Yaw angles.