Hybrid Adaptive Integrated Chassis Control

Abstract

Extensive advancements in the field of mobility and safety in transportation in last few decades
have acted as a catalyst for the expansion of automobile industry. The research for the evolution
of new technologies, vehicle safety regulations and specifications and the market requirements
has given this progress a greater push. The passenger cars these days are equipped with ample
collection of active safety systems such as Anti-lock Braking Systems (ABS), Electronic Stability
Program (ESP), Active Front Steering (AFS) and many more. The amalgamation of these active
safety systems in the vehicle chassis allows the vehicle to accomplish the desired stability.
Both academia and industry understood the requirement of more research in the field of vehicle
industry. This leads to the comprehensive enhancement in the field of research and development
with respect to integrated chassis control (ICC). The new research delivered some remarkable advantages
to this industry, such as cost reduction of the complete system, multi-objective performance
growth, hardware entanglement, fault-tolerant capability and system plausibility.
Despite the huge diversity in research of integrated chassis, there are certain adaptive design methods
which can be used to enhance the ICC performance. This dissertation intends to provide a
methodology to fully exploit the nonlinear dynamics of the vehicle concerning the forces in between
tire and road surface and to discuss the integration of AFS and ESP. It establishes a novel
adaptive control approach in order to attain asymptotic tracking for switched affine vehicle models
with parameter uncertainties and disturbances acting on the model. This, therefore, will help
to attain the desired performance. Further, comparisonwith strategies that merely exploits the linear
region of the vehicle dynamics are discussed, and performance improvements of the proposed
methodology are assessed. Finally, analytically the endurance of the prospective control strategy
is proven and simulations are conducted to validate the theoretical analysis.