Vehicle handling improvement by fuzzy explicit nonlinear tire forces parametrization

Mammar, Said; Benine-Neto, Andre; Glaser, Sebastien; Oufroukh, Naima Ait · 2011 · Crossref

DOI: 10.1109/ccdc.2011.5968442

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Summary

This paper addresses the challenge of improving vehicle handling and stability during extreme dynamic maneuvers, where lateral tire-road forces saturate and cause instabilities difficult for drivers to control. The authors propose a dynamic fuzzy output feedback controller designed to manage yaw motion by explicitly modeling the nonlinear behavior of tire forces. The motivation stems from the limitations of current Electronic Stability Control (ESC) systems, which primarily rely on independent wheel braking. The study aims to enhance safety and comfort by utilizing both front wheel steering and differential braking torque, ensuring the vehicle remains within a safe invariant set of states. The methodology employs a Takagi-Sugeno (TS) fuzzy model to represent the vehicle's lateral dynamics. The nonlinear tire forces are modeled using Pacejka’s magic formula, which captures the saturation and decreasing regions of lateral force relative to the sideslip angle. Using sector approximation, the authors derive a four-rule TS fuzzy model that explicitly handles these nonlinearities. The controller is synthesized using Linear and Bilinear Matrix Inequalities (LMI-BMI) methods, incorporating quadratic boundedness theory and Lyapunov stability to guarantee that trajectories remain within an invariant set. This approach allows for the handling of input and state constraints, such as limits on steering angle rate and braking torque, while balancing safety requirements with comfort specifications. The controller uses only yaw rate and steering angle as inputs, simplifying implementation. Simulation tests were conducted to evaluate the controller's performance during standard maneuvers, specifically the ISO 3888-2 transient maneuver and the sine with dwell maneuver, which are designed to excite nonlinear tire dynamics. The results demonstrate that the controlled vehicle successfully tracks the reference yaw rate and maintains stability. The fuzzy output feedback effectively manages the nonlinear tire forces, preventing the vehicle from entering unstable regions characterized by understeering or oversteering. The simulations confirm that the system remains within the predefined invariant set, validating the theoretical stability guarantees. The significance of this work lies in its ability to provide a robust control strategy that explicitly accounts for tire nonlinearity without requiring complex state estimation. By using a TS fuzzy model and LMI-BMI synthesis, the authors offer a solution that ensures stability and constraint satisfaction under extreme conditions. This approach improves upon traditional ESC systems by integrating steering and braking actions more effectively, potentially reducing accidents and enhancing vehicle controllability. The study contributes to the field of vehicle dynamics control by demonstrating that fuzzy logic can effectively handle the complex, nonlinear interactions between tires and the road, offering a viable path for advanced stability control systems.

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• steering pattern