Advances in contact algorithms and their application to tires

Currently used techniques for tire contact analysis are reviewed. Discussion focuses on the different techniques used in modeling frictional forces and the treatment of contact conditions. A status report is presented on a new computational strategy for the modeling and analysis of tires, including the solution of the contact problem. The key elements of the proposed strategy are: (1) use of semianalytic mixed finite elements in which the shell variables are represented by Fourier series in the circumferential direction and piecewise polynomials in the meridional direction; (2) use of perturbed Lagrangian formulation for the determination of the contact area and pressure; and (3) application of multilevel iterative procedures and reduction techniques to generate the response of the tire. Numerical results are presented to demonstrate the effectiveness of a proposed procedure for generating the tire response associated with different Fourier harmonics

Advances in Mechanical Systems Dynamics 2020

The fundamentals of mechanical system dynamics were established before the beginning of the industrial era. The 18th century was a very important time for science and was characterized by the development of classical mechanics. This development progressed in the 19th century, and new, important applications related to industrialization were found and studied. The development of computers in the 20th century revolutionized mechanical system dynamics owing to the development of numerical simulation. We are now in the presence of the fourth industrial revolution. Mechanical systems are increasingly integrated with electrical, fluidic, and electronic systems, and the industrial environment has become characterized by the cyber-physical systems of industry 4.0. Within this framework, the status-of-the-art has become represented by integrated mechanical systems and supported by accurate dynamic models able to predict their dynamic behavior. Therefore, mechanical systems dynamics will play a central role in forthcoming years. This Special Issue aims to disseminate the latest research findings and ideas in the field of mechanical systems dynamics, with particular emphasis on novel trends and applications

Model-based powertrain design and control system development for the ideal all-wheel drive electric vehicle

The transfer case based all-wheel drive electric vehicle (TCAWDEV) and dual-axle AWDEV have been investigated to balance concerns about energy consumption, drivability and stability of vehicles. However, the mentioned powertrain architectures have the torque windup issue or the wheel skidding issue. The torque windup is an inherent issue of mechanical linked all-wheel drive systems. The hydraulic motor-based or the electric motor-based ideal all-wheel drive powertrain can provide feasible solutions to the mentioned issues. An ideal AWDEV (IAWDEV) powertrain architecture and its control schemes were proposed by this research; the architecture has four independent driving motors in powertrain. The IAWDEV gives more control freedoms to implement active torque controls and traction mode controls. In essence, this research came up with the distributed powertrain concept, and developed control schemes of the distributed powertrain to replace the transfer case and differential devices. The study investigated the dual-loop motor control, the hybrid sliding mode control (HSMC) and the neural network predictive control to reduce energy consumption and achieve better drivability and stability by optimizing the torque allocation of each dependent wheel. The mentioned control schemes were respectively developed for the anti-slip, differential and yaw stability functionalities of the IAWDEV powertrain. This study also investigated the sizing method that the battery capacity was estimated by using cruise performance at 3% road grade. In addition, the model-based verification was employed to evaluate the proposed powertrain design and control schemes. The verification shows that the design and controls can fulfill drivability requirements and minimize the existing issues, including torque windup and chattering of the slipping wheel. In addition, the verification shows that the IAWDEV can harvest around two times more energy while the vehicle is running on slippery roads than the TCAWDEV and the dual-axle AWDEV; the traction control can achieve better drivability and lower energy consumption than mentioned powertrains; the mode control can reduce 3% of battery charge depleting during the highway driving test. It also provides compelling evidences that the functionalities achieved by complicated and costly mechanical devices can be carried out by control schemes of the IAWDEV; the active torque controls can solve the inherent issues of mechanical linked powertrains; the sizing method is credible to estimate the operation envelop of powertrain components, even though there is some controllable over-sizing

Automatic adjustment of tire inflation pressure through an intelligent CTIS: Effects on the vehicle lateral dynamic behavior

The paper investigates the effect of tire inflation pressure on the lateral dynamics of a passenger car, and presents a possible control-oriented methodology aimed at adapting tire pressure to the current vehicle loading condition targeting a reference characteristic. Starting from the tire characteristics at several inflation pressure levels, the paper investigates the effect of changing selectively tire pressure on each of the two axles, through theoretical calculation of the curvature gain based on the computation of the derivatives of stability, and compares the obtained sensitivity to the results of a multibody simulation model validated through on-track tests. Finally, the work presents a possible algorithm that could be implemented on-board vehicle ECU to provide, for the current loading condition of the vehicle, a tire pressure combination that targets a specific lateral dynamics characteristic. The algorithm is intended as part of the control logic of an intelligent Central Tire Inflation System (CTIS) able to adjust automatically tire pressure according to the actual vehicle working conditions

Least Squares Based Adaptive Control and Extremum Seeking with Active Vehicle Safety System Applications

On-line parameter estimation is one of the two key components of a typical adaptive control scheme, beside the particular control law to be used. Gradient and recursive least squares (RLS) based parameter estimation algorithms are the most widely used ones among others. Adaptive control studies in the literature mostly utilize gradient based parameter estimators for convenience in nonlinear analysis and Lyapunov analysis based constructive design. However, simulations and real-time experiments reveal that, compared to gradient based parameter estimators, RLS based parameter estimators, with proper selection of design parameters, exhibit better transient performance from the aspects of speed of convergence and robustness to measurement noise. One reason for the control theory researchers' preference of gradient algorithms to RLS ones is that there does not exist a well-established stability and convergence analysis framework for adaptive control schemes involving RLS based parameter estimation. Having this fact as one of the motivators, this thesis is on systematic design, formal stability and convergence analysis, and comparative numerical analysis of RLS parameter estimation based adaptive control schemes and extension of the same framework to adaptive extremum seeking, viz. adaptive search for (local) extremum points of a certain field. Extremum seeking designs apply to (i) finding locations of physical signal sources, (ii) minimum or maximum points of (vector) cost or potential functions for optimization, (iii) calculating optimal control parameters within a feedback control design. In this thesis, firstly, gradient and RLS based on-line parameter estimation schemes are comparatively analysed and a literature review on RLS estimation based adaptive control is provided. The comparative analysis is supported with a set of simulation examples exhibiting transient performance characteristics of RLS based parameter estimators, noting absence of such a detailed comparison study in the literature. The existing literature on RLS based adaptive control mostly follows the indirect adaptive control approach as opposed to the direct one, because of the difficulty in integrating an RLS based adaptive law within the direct approaches starting with a certain Lyapunov-like cost function to be driven to (a neighborhood) of zero. A formal constructive analysis framework for integration of RLS based estimation to direct adaptive control is proposed following the typical steps for gradient adaptive law based direct model reference adaptive control, but constructing a new Lyapunov-like function for the analysis. After illustration of the improved performance with RLS adaptive law via some simple numerical examples, the proposed RLS parameter estimation based direct adaptive control scheme is successfully applied to vehicle antilock braking system control and adaptive cruise control. The performance of the proposed scheme is numerically analysed and verified via Matlab/Simulink and CarSim based simulation tests. Similar to the direct adaptive control works, the extremum seeking approaches proposed in the literature commonly use gradient/Newton based search algorithms. As an alternative to these search algorithms, this thesis studies RLS based on-line estimation in extremum seeking aiming to enhance the transient performance compared to the existing gradient based extremum seeking. The proposed RLS estimation based extremum seeking approach is applied to active vehicle safety system control problems, including antilock braking system control and traction control, supported by Matlab/Simulink and CarSim based simulation results demonstrating the effectiveness of the proposed approach