Optimal preview game theory approach to vehicle stability controller design

Dynamic game theory brings together different features that are keys to many situations in control design: optimisation behaviour, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degrees-of-freedom vehicle-handling performance model is put into discrete form to develop the game equations of motion. To evaluate the developed control algorithm, CarSim with its built-in nonlinear vehicle model along with the Pacejka tire model is used. The control algorithm is evaluated for a lane change manoeuvre, and the optimal set of steering angle and corrective yaw moment is calculated and fed to the test vehicle. Simulation results show that the optimal preview control algorithm can significantly reduce lateral velocity, yaw rate, and roll angle, which all contribute to enhancing vehicle stability.     

Stability enhancement and fuel economy of the 4-wheel-drive hybrid electric vehicles by optimal tyre force distribution

In this paper, vehicle stability control and fuel economy for a 4-wheel-drive hybrid vehicle are investigated. The integrated controller is designed within three layers. The first layer determines the total yaw moment and total lateral force made by using an optimal controller method to follow the desired dynamic behaviour of a vehicle. The second layer determines optimum tyre force distribution in order to optimise tyre usage and find out how the tyres should share longitudinal and lateral forces to achieve a target vehicle response under the assumption that all four wheels can be independently steered, driven, and braked. In the third layer, the active steering, wheel slip, and electrical motor torque controllers are designed. In the front axle, internal combustion engine (ICE) is coupled to an electric motor (EM). The control strategy has to determine the power distribution between ICE and EM to minimise fuel consumption and allowing the vehicle to be charge sustaining. Finally, simulations performed in MATLAB/SIMULINK environment show that the proposed structure could enhance the vehicle stability and fuel economy in different manoeuvres.     

Analytical solutions for optimal ride comfort and tyre grip for passive vehicle suspensions

The paper derives analytical solutions for the global optimum of the ride comfort and tyre grip performance measures for a quarter-car vehicle model optimised both individually and in combination. The solutions are derived for six simple suspension networks comprising one or two springs, one damper and possibly one inerter. The solutions are functions of four vehicle parameters: the sprung mass, the unsprung mass, the tyre stiffness and the static stiffness, of the suspension.     

A method for estimation of vehicle inertial parameters

In this paper, a new method is presented for estimating the current sprung mass inertial parameters of a vehicle, such as the mass, pitch and roll mass moments of inertia, and lateral and longitudinal centre of gravity locations. The method measures the sprung mass response when the vehicle is driven over an unknown and unmeasured random road profile. From these measurements, the equivalent free-decay responses are extracted and modal analysis techniques used to estimate the sprung mass natural frequencies, damping ratios and mode shapes. This information is combined with a simplified vehicle estimation model, least squares analysis and known equivalent stiffness parameters to estimate the vehicles’ inertial parameters. The results obtained from several simulation examples show that estimates of the inertial parameters generally have small relative errors.     

Model predictive control with constraints for a nonlinear adaptive cruise control vehicle model in transition manoeuvres

A vehicle following control law, based on the model predictive control method, to perform transition manoeuvres (TMs) for a nonlinear adaptive cruise control (ACC) vehicle is presented in this paper. The TM controller ultimately establishes a steady-state following distance behind a preceding vehicle to avoid collision, keeping account of acceleration limits, safe distance, and state constraints. The vehicle dynamics model is for continuous-time domain and captures the real dynamics of the sub-vehicle models for steady-state and transient operations. The ACC vehicle can execute the TM successfully and achieves a steady-state in the presence of complex dynamics within the constraint boundaries.     

Vehicle yaw stability control using active limited-slip differential via model predictive control methods

In this paper, the problem of vehicle yaw control using an active limited-slip differential (ALSD) applied on the rear axle is addressed. The controller objective is to minimise yaw-rate and body slip-angle errors, with respect to target values. A novel model predictive controller is designed, using a linear parameter-varying (LPV) vehicle model, which takes into account the ALSD dynamics and its constraints. The controller is simulated using a 10DOF Matlab/Simulink simulation model and a CarSim model. These simulations exemplify the controller yaw-rate and slip-angle tracking performances, under challenging manoeuvres and road conditions. The model predictive controller performances surpass those of a reference sliding mode controller, and can narrow the loss of performances due to the ALSD's inability to transfer torque regardless of driving conditions.     

Design of a feedback-feedforward steering controller for accurate path tracking and stability at the limits of handling

This paper presents a feedback-feedforward steering controller that simultaneously maintains vehicle stability at the limits of handling while minimising lateral path tracking deviation. The design begins by considering the performance of a baseline controller with a lookahead feedback scheme and a feedforward algorithm based on a nonlinear vehicle handling diagram. While this initial design exhibits desirable stability properties at the limits of handling, the steady-state path deviation increases significantly at highway speeds. Results from both linear and nonlinear analyses indicate that lateral path tracking deviations are minimised when vehicle sideslip is held tangent to the desired path at all times. Analytical results show that directly incorporating this sideslip tangency condition into the steering feedback dramatically improves lateral path tracking, but at the expense of poor closed-loop stability margins. However, incorporating the desired sideslip behaviour into the feedforward loop creates a robust steering controller capable of accurate path tracking and oversteer correction at the physical limits of tyre friction. Experimental data collected from an Audi TTS test vehicle driving at the handling limits on a full length race circuit demonstrates the improved performance of the final controller design.     

An efficient approach to the analysis of rail surface irregularities accounting for dynamic train–track interaction and inelastic deformations

A two-dimensional computational model for assessment of rolling contact fatigue induced by discrete rail surface irregularities, especially in the context of so-called squats, is presented. Dynamic excitation in a wide frequency range is considered in computationally efficient time-domain simulations of high-frequency dynamic vehicle–track interaction accounting for transient non-Hertzian wheel–rail contact. Results from dynamic simulations are mapped onto a finite element model to resolve the cyclic, elastoplastic stress response in the rail. Ratcheting under multiple wheel passages is quantified. In addition, low cycle fatigue impact is quantified using the Jiang–Sehitoglu fatigue parameter. The functionality of the model is demonstrated by numerical examples.     

Vehicle control synthesis using phase portraits of planar dynamics

ABSTRACT

Phase portraits provide control system designers strong graphical insight into nonlinear system dynamics. These plots readily display vehicle stability properties and map equilibrium point locations and movement to changing parameters and system inputs. This paper extends the usage of phase portraits in vehicle dynamics to control synthesis by illustrating the relationship between the boundaries of stable vehicle operation and the state derivative isoclines in the yaw rate–sideslip phase plane. Closed-loop phase portraits demonstrate the potential for augmenting a vehicle's open-loop dynamics through steering and braking. The paper concludes by applying phase portrait analysis to an envelope control algorithm for yaw stability and a sliding surface controller for stabilising a saddle point equilibrium in drifting.     

Policy challenges of increasing automation in driving

The convergence of information and communication technologies (ICT) with automotive technologies has already resulted in automation features in road vehicles and this trend is expected to continue in the future owing to consumer demand, dropping costs of components, and improved reliability. While the automation features that have taken place so far are mainly in the form of information and driver warning technologies (classified as level I pre-2010), future developments in the medium term (level II 2010–2025) are expected to exhibit connected cognitive vehicle features and encompass increasing degree of automation in the form of advanced driver assistance systems. Although autonomous vehicles have been developed for research purposes and are being tested in controlled driving missions, the autonomous driving case is only a long term (level III 2025 +) scenario. This paper contributes knowledge on technological forecasts regarding automation, policy challenges for each level of technology development and application context, and the essential instrument of cost-effectiveness for policy analysis which enables policy decisions on the automation systems to be assessed in a consistent and balanced manner. The cost of a system per vehicle is viewed against its effectiveness in meeting policy objectives of improving safety, efficiency, mobility, convenience and reducing environmental effects. Example applications are provided that illustrate the contribution of the methodology in providing information for supporting policy decisions. Given the uncertainties in system costs as well as effectiveness, the tool for assessing policies for future generation features probabilistic and utility-theoretic analysis capability. The policy issues defined and the assessment framework enable the resolution of policy challenges while allowing worthy innovative automation in driving to enhance future road transportation.