Vehicle Dynamics, Lateral Forces, Roll Angle, Tire Wear and Road Profile States Estimation - A Review

Estimation of vehicle dynamics, tire wear, and road profile are indispensable prefaces in the development of automobile manufacturing due to the growing demands for vehicle safety, stability, and intelligent control, economic and environmental protection. Thus, vehicle state estimation approaches have captured the great interest of researchers because of the intricacy of vehicle dynamics and stability control systems. Over the last few decades, great enhancement has been accomplished in the theory and experiments for the development of these estimation states. This article provides a comprehensive review of recent advances in vehicle dynamics, tire wear, and road profile estimations. Most relevant and significant models have been reviewed in relation to the vehicle dynamics, roll angle, tire wear, and road profile states. Finally, some suggestions have been pointed out for enhancing the performance of the vehicle dynamics models

The FX/90: A proposal in response to a low Reynolds Number station keeping mission

The FX/90 is a remotely piloted vehicle designed to fly at Reynolds numbers below 2 x 10 to the 5th power. Several applications exist for this type of flight, such as low altitude flight of very small aircraft. The design presented here allows investigation into the unique problems involved in low Reynolds number flight, which will, in turn, further understanding of this flight regime. The aircraft will operate in a steady flight environment, free from significant atmospheric turbulence and weather effects. The F-90 has a 39 in. fuselage which is constructed of balsa and plywood. The landing gear for the aircraft is a detachable carriage on which the aircraft rests. The aerodynamic planform is a rectangular wing (no taper or sweep) with a chord of 9 in., a wingspan of 72 in., and is constructed entirely out of styrofoam. The propulsion system is a puller configuration mounted on the front of the fuselage. It consists of an Astro 05 engine and a 10-6 two bladed propeller. Control of the aircraft is accomplished through the use of two movable control surfaces: elevators for pitch control, and a rudder for yaw control. The aircraft is soundly constructed, highly maneuverable, and adequately powered. Furthermore, the investigation into alternative technologies, most notably the styrofoam wing and the detachable landing gear, holds promise to improve the performance of the aircraft

Robust and Regularized Algorithms for Vehicle Tractive Force Prediction and Mass Estimation

This work provides novel robust and regularized algorithms for parameter estimation with applications in vehicle tractive force prediction and mass estimation. Given a large record of real world data from test runs on public roads, recursive algorithms adjusted the unknown vehicle parameters under a broad variation of statistical assumptions for two linear gray-box models

Optimal fault-tolerant flight control for aircraft with actuation impairments

Current trends towards greater complexity and automation are leaving modern technological systems increasingly vulnerable to faults. Without proper action, a minor error may lead to devastating consequences. In flight control, where the controllability and dynamic stability of the aircraft primarily rely on the control surfaces and engine thrust, faults in these effectors result in a higher extent of risk for these aspects. Moreover, the operation of automatic flight control would be suddenly disturbed. To address this problem, different methodologies of designing optimal flight controllers are presented in this thesis. For multiple-input multiple-output (MIMO) systems, the feedback optimal control is a prominent technique that solves a multi-objective cost function, which includes, for instance, tracking requirements and control energy minimisation. The first proposed method is based on a linear quadratic regulator (LQR) control law augmented with a fault-compensation scheme. This fault-tolerant system handles the situation in an adaptive way by solving the optimisation cost function and considering fault information, while assuming an effective fault detection system is available. The developed scheme was tested in a six-degrees-of-freedom nonlinear environment to validate the linear-based controller. Results showed that this fault tolerant control (FTC) strategy managed to handle high magnitudes of the actuator’s loss of effciency faults. Although the rise time of aircraft response became slower, overshoot and settling errors were minimised, and the stability of the aircraft was maintained. Another FTC approach has been developed utilising the features of controller robustness against the system parametric uncertainties, without the need for reconfiguration or adaptation. Two types of control laws were established under this scheme, the H∞ and µ-synthesis controllers. Both were tested in a nonlinear environment for three points in the flight envelope: ascending, cruising, and descending. The H∞ controller maintained the requirements in the intact case; while in fault, it yielded non-robust high-frequency control surface deflections. The µ-synthesis, on the other hand, managed to handle the constraints of the system and accommodate faults reaching 30% loss of effciency in actuation. The final approach is based on the control allocation technique. It considers the tracking requirements and the constraints of the actuators in the design process. To accommodate lock-in-place faults, a new control effort redistribution scheme was proposed using the fuzzy logic technique, assuming faults are provided by a fault detection system. The results of simulation testing on a Boeing 747 multi-effector model showed that the system managed to handle these faults and maintain good tracking and stability performance, with some acceptable degradation in particular fault scenarios. The limitations of the controller to handle a high degree of faults were also presented

Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact

Recent trends in vehicle engineering are testament to the great efforts that scientists and industries have made to seek solutions to enhance both the performance and safety of vehicular systems. This Special Issue aims to contribute to the study of modern vehicle dynamics, attracting recent experimental and in-simulation advances that are the basis for current technological growth and future mobility. The area involves research, studies, and projects derived from vehicle dynamics that aim to enhance vehicle performance in terms of handling, comfort, and adherence, and to examine safety optimization in the emerging contexts of smart, connected, and autonomous driving.This Special Issue focuses on new findings in the following topics:(1) Experimental and modelling activities that aim to investigate interaction phenomena from the macroscale, analyzing vehicle data, to the microscale, accounting for local contact mechanics; (2) Control strategies focused on vehicle performance enhancement, in terms of handling/grip, comfort and safety for passengers, motorsports, and future mobility scenarios; (3) Innovative technologies to improve the safety and performance of the vehicle and its subsystems; (4) Identification of vehicle and tire/wheel model parameters and status with innovative methodologies and algorithms; (5) Implementation of real-time software, logics, and models in onboard architectures and driving simulators; (6) Studies and analyses oriented toward the correlation among the factors affecting vehicle performance and safety; (7) Application use cases in road and off-road vehicles, e-bikes, motorcycles, buses, trucks, etc

Comparative study of two dynamics-model-based estimation algorithms for distributed drive electric vehicles

The effect of vehicle active safety systems is subject to the accurate knowledge of vehicle states. Therefore, it is of great importance to develop a precise and robust estimation approach so as to deal with nonlinear vehicle dynamics systems. In this paper, a planar vehicle model with a simplified tire model is established first. Two advanced model-based estimation algorithms, an unscented Kalman filter and a moving horizon estimation, are developed for distributed drive electric vehicles. Using the proposed algorithms, vehicle longitudinal velocity, lateral velocity, yaw rate as well as lateral tire forces are estimated based on information fusion of standard sensors in today’s typical vehicle and feedback signals from electric motors. Computer simulations are implemented in the environment of CarSim combined with Matlab/Simulink. The performance of both estimators regarding convergence, accuracy, and robustness against an incorrect initial estimate of longitudinal velocity is compared in detail. The comparison results demonstrate that both estimation approaches have favourable coincidence with the corresponding reference values, while the moving horizon estimation is more accurate and robust, and owns faster convergence.DFG, 325093850, Open Access Publizieren 2017 - 2018 / Technische Universität Berli

Full Vehicle State Estimation Using a Holistic Corner-based Approach

Vehicles' active safety systems use different sensors, vehicle states, and actuators, along with an advanced control algorithm, to assist drivers and to maintain the dynamics of a vehicle within a desired safe range in case of instability in vehicle motion. Therefore, recent developments in such vehicle stability control and autonomous driving systems have led to substantial interest in reliable road angle and vehicle states (tire forces and vehicle velocities) estimation. Advances in applications of sensor technologies, sensor fusion, and cooperative estimation in intelligent transportation systems facilitate reliable and robust estimation of vehicle states and road angles. In this direction, developing a flexible and reliable estimation structure at a reasonable cost to operate the available sensor data for the proper functioning of active safety systems in current vehicles is a preeminent objective of the car manufacturers in dealing with the technological changes in the automotive industry. This thesis presents a novel generic integrated tire force and velocity estimation system at each corner to monitor tire capacities and slip condition individually and to address road uncertainty issues in the current model-based vehicle state estimators. Tire force estimators are developed using computationally efficient nonlinear and Kalman-based observers and common measurements in production vehicles. The stability and performance of the time-varying estimators are explored and it is shown that the developed integrated structure is robust to model uncertainties including tire properties, inflation pressure, and effective rolling radius, does not need tire parameters and road friction information, and can transfer from one car to another. The main challenges for velocity estimation are the lack of knowledge of road friction in the model-based methods and accumulated error in kinematic-based approaches. To tackle these issues, the lumped LuGre tire model is integrated with the vehicle kinematics in this research. It is shown that the proposed generic corner-based estimator reduces the number of required tire parameters significantly and does not require knowledge of the road friction. The stability and performance of the time-varying velocity estimators are studied and the sensitivity of the observers' stability to the model parameter changes is discussed. The proposed velocity estimators are validated in simulations and road experiments with two vehicles in several maneuvers with various driveline configurations on roads with different friction conditions. The simulation and experimental results substantiate the accuracy and robustness of the state estimators for even harsh maneuvers on surfaces with varying friction. A corner-based lateral state estimation is also developed for conventional cars application independent of the wheel torques. This approach utilizes variable weighted axles' estimates and high slip detection modules to deal with uncertainties associated with longitudinal forces in large steering. Therefore, the output of the lateral estimator is not altered by the longitudinal force effect and its performance is not compromised. A method for road classification is also investigated utilizing the vehicle lateral response in diverse maneuvers. Moreover, the designed estimation structure is shown to work with various driveline configurations such as front, rear, or all-wheel drive and can be easily reconfigured to operate with different vehicles and control systems' actuator configurations such as differential braking, torque vectoring, or their combinations on the front or rear axles. This research has resulted in two US pending patents on vehicle speed estimation and sensor fault diagnosis and successful transfer of these patents to industry

Development of an Integrated Estimation Method for Vehicle States, Parameters and Tire Forces

Stability and desirable performance of vehicle control systems are directly dependent on the quality and accuracy of sensory and estimated data provided to the controllers. Tire forces and vehicle states such as lateral and longitudinal velocities are required information for most vehicle control systems. However, there are challenges associated with efficient estimation of tire forces and vehicle states. Furthermore, changes in vehicle inertial parameters, road grade, and bank angle all have major influences on both tire forces and vehicle states. Efficient identification of these parameters requires sufficient information about a set of vehicle states and tire forces. This duality relationship mandates the development of efficient methods for simultaneous estimation of tire forces, vehicle states, and vehicle and road parameters. This research proposes the design of an integrated estimation structure that can simultaneously estimate tire forces, vehicle velocity, vehicle inertial parameters, and road angles. The proposed structure is robust against variations in tire parameters because of tire brand, wear, and road friction coefficient. The methods developed in this thesis are all validated experimentally on multiple vehicle platform.4 month

Advanced Sensing and Control for Connected and Automated Vehicles

Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs

Mathematical modelling, flight control system design and air flow control investigation for low speed UAVs

The demand for unmanned aerial vehicles (UAVs) has increased dramatically in the last decade from reconnaissance missions to attack roles. As their missions become more complex, advances in endurance and manoeuvrability become crucial. Due to the advances in material fabrication, wing morphing can be seen as an ideal solution for UAVs to provide improvements by overcoming the weight drawback. This thesis investigates the area of aircraft design and simulation for low speed UAVs looking at performance enhancements techniques for low speed UAVs, and their effects on the aerodynamic capabilities of the wing. The focus is on both suitable control design and wing morphing techniques based on current research findings. The low speed UAV X-RAE1 is used as the test bed for this investigation and is initially analytically presented as three dimensional body where the equations relate to the forces and moments acting on the UAV. A linearised model for straight flight at different velocities is implemented and validated against a non-linear model. Simulations showed the X-RAE1 to have acceptable stability properties over the design operating range. Control design techniques, linear quadratic regulators (LQR) and H-infinity optimisation with Loop Shaping Design Procedure (LSDP), are used to design simple control schemes for linearised longitudinal model of the X-RAE1 UAV at different velocities. The effectiveness and limitations of the two design methods show that both designs are very fast, with settling times 2-3 seconds in the height response and remarkably low variation of the results at different velocities. Computational fluid dynamics is then used to investigate and simulate the impact of introducing smart effector arrays on a UAV. The smart effector array produces a form of active flow control by providing localised flow field changes. These induced changes have direct impact on the aerodynamic forces and showed a substantial increase of lift at low angles of attack. There was also a significant increase to the lift to drag ratio at high angles of attack which resulted to a delay in stall