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This paper discusses observability of the vehicle states using different sensor configurations as well as fault-tolerant estimation of these states. The optimality of the sensor configurations is assessed through different observability measures and by using a 3-DOF linear vehicle model that incorporates yaw, roll and lateral motions of the vehicle. The most optimal sensor configuration is adopted and an observer is designed to estimate the states of the vehicle handling dynamics. Robustness of the observer against sensor failure is investigated. A fault-tolerant adaptive estimation algorithm is developed to mitigate any possible faults arising from the sensor failures. Effectiveness of the proposed fault-tolerant estimation scheme is demonstrated through numerical analysis and CarSim simulation.

This paper presents the implementation of an off-line optimized torque vectoring controller on an electric-drive vehicle with four in-wheel motors for driver assistance and handling performance enhancement. The controller takes vehicle longitudinal, lateral, and yaw acceleration signals as feedback using the concept of state-derivative feedback control. The objective of the controller is to optimally control the vehicle motion according to the driver commands. Reference signals are first calculated using a driver command interpreter to accurately interpret what the driver intends for the vehicle motion. The controller then adjusts the braking/throttle outputs based on discrepancy between the vehicle response and the interpreter command.

The optimum driving dynamics can be achieved only when the tire forces on all four wheels and in all three coordinate directions are monitored and controlled precisely. This advanced level of control is possible only when a vehicle is equipped with several active chassis control systems that are networked together in an integrated fashion. To investigate such capabilities, an electric vehicle model has been developed with four direct-drive in-wheel motors and an active steering system. Using this vehicle model, an advanced slip control system, an advanced torque vectoring controller, and a genetic fuzzy active steering controller have been developed previously. This paper investigates whether the integration of these stability control systems enhances the performance of the vehicle in terms of handling, stability, path-following, and longitudinal dynamics.

A two-passenger, all-wheel-drive urban electric vehicle (AUTO21EV) with four direct-drive in-wheel motors has been designed and developed at the University of Waterloo. A 14-degree-of-freedom model of this vehicle has been used to develop a genetic fuzzy yaw moment controller. The genetic fuzzy yaw moment controller determines the corrective yaw moment that is required to stabilize the vehicle, and applies a virtual yaw moment around the vertical axis of the vehicle. In this work, an advanced torque vectoring controller is developed, the objective of which is to generate the required corrective yaw moment through the torque intervention of the individual in-wheel motors, stabilizing the vehicle during both normal and emergency driving maneuvers. Novel algorithms are developed for the left-to-right torque vectoring control on each axle and for the front-to-rear torque vectoring distribution action.

This paper proposes a model-based “Cascaded Dual Extended Kalman Filter” (CDEKF) for combined vehicle state estimation, namely, tire vertical forces and parameter identification. A sensitivity analysis is first carried out to recognize the vehicle inertial parameters that have significant effects on tire normal forces. Next, the combined estimation process is separated in two components. The first component is designed to identify the vehicle mass and estimate the longitudinal forces while the second component identifies the location of center of gravity and estimates the tire normal forces. A Dual extended Kalman filter is designed for each component for combined state estimation and parameter identification. Simulation results verify that the proposed method can precisely estimate the tire normal forces and accurately identify the inertial parameters.

This study proposes a novel semi-active hydro-pneumatic suspension design and investigates its performance potentials. The proposed new semi-active suspension design involves pneumatic interconnection between the front and rear suspension struts of the vehicle. The analytical formulations of suspension forces due to two suspension configurations, a passive unconnected and the proposed semi-active interconnected, are derived to analyze suspension properties. Based on a validated pitch-plane vehicle braking model, vehicle dynamic responses are conducted under a range of measured road roughness excitations and driving speeds, as well as braking inputs.

This study investigates influence of compressible hydraulic fluid and suspension floating piston dynamics of fluidic suspensions on heavy vehicle roll stability and ride dynamics. Two fluidic suspension designs, including a single-gas-chamber strut and a novel twin-gas-chamber strut, are analyzed to develop the mathematical formulations of dynamic forces, upon considerations of hydraulic fluid compressibility and floating piston dynamics. Dynamic responses of the heavy vehicle with the different suspension configurations are then performed using a nonlinear roll plane vehicle model. The excitations arise from vehicle-road interactions as well as a steady steering maneuver. The results demonstrate that the compressibility characteristic of hydraulic fluid within a hydro-pneumatic suspension could affect the vehicle roll stability and ride dynamics, while the influence of suspension floating piston dynamics on vehicle dynamic responses is negligible.

The ride performance potentials of a prototype torsio-elastic axle suspension for an off-road vehicle were investigated analytically and experimentally. A forestry vehicle was fitted with the prototype suspension at its rear axle to assess its ride performance benefits. Field measurements of ride vibration along the vertical, lateral, fore-aft, roll and pitch axes were performed for the suspended and an unsuspended vehicle, while traversing a forestry terrain. The measured vibration responses of both vehicles were evaluated in terms of unweighted and frequency-weighted rms accelerations and the acceleration spectra, and compared to assess the potential performance benefits of the proposed suspension. The results revealed that the proposed suspension could yield significant reductions in the vibration magnitudes transmitted to the operator's station.