A receding horizon sliding control approach for electric powertrains with backlash and flexible half-shafts

Active control of electric powertrains is challenging, due to the fact that backlash and structural flexibility in transmission components can cause severe performance degradation or even instability of the control system. Furthermore, high impact forces in transmissions reduce driving comfort and possibly lead to damage of the mechanical elements in contact. In this paper, a nonlinear electric powertrain is modelled as a piecewise affine (PWA) system. The novel receding horizon sliding control (RHSC) idea is extended to constrained PWA systems and utilised to systematically address the active control problem for electric powertrains. Simulations are conducted in Matlab/Simulink in conjunction with the high fidelity Carsim software. RHSC shows superior jerk suppression and target wheel speed tracking performance as well as reduced computational cost over classical model predictive control (MPC). This indicates the newly proposed RHSC is an effective method to address the active control problem for electric powertrains.     

Advanced Control Methods for Automotive Applications

This paper reviews key developments in applications of advanced control methods to automotive systems. Such applications appear in many aspects of vehicle controls. We will examine representative application areas, which include engines, suspension systems, traction systems, steering systems and those for automated highway systems (AHS). Each area is examined from the viewpoint of modeling and control algorithm development. Useful control theories for automotive application are briefly reviewed for better understanding of the applicability of these theories.     

Estimation of Tire-Road Friction Using Observer Based Identifiers

This paper presents methods for identifying the tire-road friction coefficient. The proposed methods are: an observer-based least square method and an observer/filtered-regressor-based method. These methods were designed assuming that some of the states are not available since physical parameter identification methods developed assuming that the system states are available are not attractive from a practical point of view. The observer is used to estimate signals which are difficult or expensive to measure. Using the estimated states of the system and the filtered-regressor, the parameter estimates are obtained. The proposed methods are evaluated on an eight state nonlinear vehicle/transmission simulation model with a Bakker-Pacejka's formula tire model. Vehicle tests have been performed on dry and wet roads to verify the performance of the methods. It has been shown through simulations and vehicle tests how the RPM sensors can be used with observer based identification methods to estimate the tire-road friction from measurements of engine rpm, transmission output speed and wheel speed. The proposed methods will be useful in the implementation and adaptation of vehicle collision warning/avoidance algorithm since the tire-road friction can be estimated only using the RPM sensors which are currently being used in production vehicles.     

Energy Dissipation Due to Vehicle/Track Interaction

The effects of track irregularities and wheel profile on the amount of energy dissipated in railroad freight vehicles is examined. A nonlinear computational model is used to determine the average dissipation in the vehicle suspension and the wheel/rail contact patches. This dissipation is a component of the total resistance force acting on the vehicle. Parametric results are presented showing the effects of track geometry, wheel profile, suspension design, and hunting on train resistance. Track geometry studies consider the effects of track quality and curving. The AAR 1:20 wheel profile and the Heumann wheel profile are compared under various operating conditions. Compared with the Heumann profile, the AAR 1:20 profile is shown to have lower average resistance on good quality tangent track, but higher average resistance in steady curves. A trade-off exists between the two profiles when dynamic curve entry is considered.     

An experimental testbed for mobile offshore base control concepts

 The concept of a mobile offshore base (MOB) reflects the need to stage and support military and humanitarian operations anywhere in the world. A MOB is a self-propelled, modular, floating platform that can be assembled into lengths of up to 2 km, as required, to provide logistic support to US military operations where fixed bases are not available or adequate. It accommodates the take-off and landing of C17 aircraft, and can be used for storage, as well as to send resources quickly to shore. In most concepts, the structure is made of three to five modules, which have to perform long-term station-keeping in the presence of winds, waves, and currents. This is usually referred to as dynamic positioning (DP). In the MOB, the alignment is maintained through the use of thrusters, connectors, or a combination of both. In this paper, we consider the real-time control of scaled models of a MOB. The modules are built at the 1 : 150 scale, and are kept aligned by rotating thrusters under a hierarchical hybrid control scheme. This paper describes a physical testbed developed at the University of California, Berkeley, under a grant from the US Office of Naval Research, for the purpose of evaluating competing MOB control concepts. Received: June 4, 2002 / Accepted: October 30, 2002 Acknowledgments. This material is based on work supported by the MOB Program of the US Office of Naval Research under grant N00014-98-1-0744. The authors would like to thank the Link Foundation for its support. Many thanks go to Stephen Spry for his experimental work. The photographs are courtesy of Bill Stone, Gerald Stone, and Jay Sullivan of the PATH Publications staff. Address correspondence to: A.R. Girard (e-mail: anouck@eecs.berkeley.edu)     

High Speed Stability for Rail Vehicles Considering Varying Conicity and Creep Coefficients

The critical or hunting speed of solid axle rail vehicles is known to be a strong function of primary suspension stiffness, wheel/rail profile geometry (conicity and gravitational stiffness), wheel/rail friction forces (creep coefficients), bogie/carbody inertia properties, and secondary suspension design. This paper deals with the problem of maximizing the critical speed through design of the primary and secondary suspension but with control only over the range of wheel/rail geometry and friction characteristics. For example, the conicity may varie from .05 to .3 and the linear creep coefficients from 25% to 100% of the predicted Kalker values.

It is shown that the maximum critical speed is greatly limited by the wheel/rail geometry and friction variations. It is also shown that, when lateral curving and ride quality are considered, the best design approach is to select an intermediate primary longitudinal stiffness, to limit the lowest value of conicity (e.g. to .1 or .2) by wheel profile redesign, increasing the secondary yaw damping value (yaw relaxation) and optimizing the primary and secondary lateral stiffness.     

Forced Steering of Rail Vehicles: Stability and Curving Mechanics

A forced steering rail vehicle employs linkages between.the carbody and wheelsets to force a more radial wheelset alignment. It is shown that the curve negotiation capability of forced steering trucks is significantly improved over conventional and self steering radial trucks. Parametric curves are presented showing angle-of-attack and lateral flange force as a function of steering gain parameters and truck bending stiffness. It is also shown that the forced steering concept can produce kinematic instability and severely reduced critical speeds for low conicities and creep coefficients. Analytic expressions are derived that illustrate how these kinematic instabilities can be avoided.     

Cooperative Estimation Using Vehicle Communications

Summary Each vehicle on a section of highway is potentially a driving condition 'sensor.' For example, a vehicle's speed give can give a clue about the traffic conditions in its section of roadway. By 'cooperative estimation,' we mean a system that uses a communication network to combine the experience of many vehicles into parameter estimates that are more useful than the estimates that any individual vehicle could generate by itself. This paper demonstrates the cooperative estimation concept by showing how it can be used to estimate traffic conditions and road friction without using roadside sensors.