Edward Holweg

Hybrid ABS Control Using Force Measurement

The anti-lock braking system (ABS) is the most important active safety system for passenger cars. Thanks to tire force measurement, provided for example by the new SKF load sensing hub bearing units, hybrid ABS algorithms can be made simpler and more robust than when only using wheel acceleration measurement. A two-phase algorithm is presented, where the wheel acceleration is controlled in closed-loop and the longitudinal force measurement is used to fire phase switching. Load transfer is accounted for using the vertical force measurement. Realistic simulations show that this simple algorithm can handle changes in vehicle velocity and tire-road friction without extra logic or adaptation of the controller parameters. Stability analysis provides tuning indications. Finally, the algorithm is validated on a tire-in-the-loop experimental facility.

Closed-Loop Subspace Predictive Control for Fault Tolerant MPC Design

Abstract Subspace predictive control (SPC) is recently seen in the literature for joint system identification and control design. This combination enables automatically tuning the parameters in conventional model predictive control (MPC); and therefore provides a solution to the problem of fault tolerant MPC design. The existing SPCs either deal with open-loop data or depend on the information of the controller in a closed loop. In this paper we introduce a new closed-loop SPC method, which is independent of any controller information. Both the analytic solution to the unconstrained case and the quadratic programming problem for the constrained case are formulated. A recursive solution for updating the SPC control law is proposed. A fault tolerant MPC scheme is then developed based on the recursive algorithm, whose effectiveness is demonstrated on tolerating a fault in a steer-by-wire actuator.

Steering Force Feedback for Human–Machine-Interface Automotive Experiments

Driving-simulator fidelity is usually defined by the quality of its visual and motion cueing system. However, the quality of its haptic cues is also very important and is determined by both hardware and control properties. Most experiments with haptic steering systems employ commercially available systems and do not address the systems fidelity. The goal of this paper is to offer guidelines for the development of hardware, performance evaluation, and system control in order to engineer realistic haptic cues on the steering wheel. A relatively low-cost solution for hardware is deployed, consisting of a velocity-controlled three-phase brushless servomotor, of which its high-bandwidth control allows for a realistic representation of forces. A method is presented to overcome electromagnetic interference produced by the industrial servomotor and the controller through careful amplification and filtering. To test the system, different inertia-spring-damper systems were simulated and evaluated in time and frequency domain. In conclusion, the designed system allowed reproduction of a large range of steering-wheel dynamics and forces. As a result, the developed system constitutes an efficient haptic device for human-machine-interface automotive experiments.

Race-Car Instrumentation for Driving Behavior Studies

This paper supplies a roadmap on how a researcher can effectively perform real vehicular experiments oriented to high-speed driving research. It provides detailed guidelines for constructing versatile low-cost instrumentation suitable to be fitted on race cars. The custom-built equipment, consisting of wheel-speed sensors, steering angle-torque sensors, electronic boards, etc., is thoroughly described. Furthermore, this paper depicts the required processing from raw measurements to user-friendly data suitable for driver behavior studies. As an illustration, a case study on driving behavior analysis is presented, during the execution of high-speed circular maneuvers. The recorded data showed markedly different driving behaviors between expert and novice drivers. The mechanical designs and the open-source-based software are freely available online.

On the performance increase of wheel deceleration control through force sensing

This paper presents a hybrid ABS controller based on wheel deceleration and force sensing. The proposed controller consists of a deceleration based switching logic that stabilizes the wheel slip dynamics around a limit cycle and a force measurement based algorithm that updates the maximum and minimum braking torque. It is shown how force sensing can improve performance and, at the same time, yield a simpler controller with respect to traditional ABS. Experimental tests validate the proposed design.

Lateral vehicle dynamics control based on tyre utilization coefficients and tyre force measurements

In assessing and controlling vehicle dynamics, tyre forces are the most important variables as they are the only point of interaction with the road. Estimating tyre forces is difficult for their nonlinear characteristics and most vehicle dynamics controllers are therefore based on indirect measurements as yaw rate. With the invention of tyre force sensors, direct measurement of tyre forces is possible. In this work, a tyre force based lateral vehicle dynamics controller is proposed. The controller, applying an independent steering correction, controls the lateral tyre forces so to better distribute the force on the four tyres. This is obtained equating the tyre utilization coefficients. The proposed controller is tested in a simulation environment using CarSim and Simulink.

Sliding mode-based lateral vehicle dynamics control using tyre force measurements

In this work, a lateral vehicle dynamics control based on tyre force measurements is proposed. Most of the lateral vehicle dynamics control schemes are based on yaw rate whereas tyre forces are the most important variables in vehicle dynamics as tyres are the only contact points between the vehicle and road. In the proposed method, active front steering is employed to uniformly distribute the required lateral force among the front left and right tyres. The force distribution is quantified through the tyre utilisation coefficients. In order to address the nonlinearities and uncertainties of the vehicle model, a gain scheduling sliding-mode control technique is used. In addition to stabilising the lateral dynamics, the proposed controller is able to maintain maximum lateral acceleration. The proposed method is tested and validated on a multi-body vehicle simulator.

Design issues for haptic steering force feedback on an automotive simulator

This paper describes the deployment of a torque controlled force feedback steering device for human in the loop automotive simulations. The high bandwidth of the velocity controlled three phase brushless servomotor allows for a realistic representation of the virtual dynamics. The electromagnetic interference produced by the industrial servomotor and the controller made the elaboration stage challenging. To overcome the former issues careful amplification and filtering was ineluctable. The final dynamical model of the steering system used and the corresponding motor controller constitute an efficient haptic device for providing intuitive kinesthetic feedback. The system can feed back torques up to 20NM with accuracy of 0.02NM.

Solving Algebraic Riccati Equation real time for Integrated Vehicle Dynamics Control

In this paper we present a comparison study of different computational methods to implement State Dependent Riccati Equation (SDRE) based control in real time for a vehicle dynamics control application. Vehicles are mechatronic systems with nonlinear dynamics. One of the promising nonlinear control methods to control vehicle dynamics is based on SDRE. In this method, an Algebraic Riccati Equation (ARE) is solved at each sample to generate the control signal. However solving ARE is computationally complex. In this work, Extended Kalman Filter (EKF) iterative, Schur, Eigenvector, and Hamiltonian methods to solve ARE real time are implemented and studied for their timing, accuracy, and feasibility. Three methods, Schur, Eigenvector, and Hamiltonian are found to have an average calculation time of 3.9, 2.5, and 1.6 milliseconds on a dSPACE real time processor. This timing is acceptable as the controller sampling time is 10 milliseconds. In addition to the least processing time, the Hamiltonian based approach yields the lowest quadratic cost for SDRE based Integrated Vehicle Dynamics Control (IVDC).

Vehicle sideslip estimation using tyre force measurements

Estimating vehicle sideslip is challenging as well as important for vehicle safety systems such as Electronic Stability Control. In this work, a Kalman filter is proposed to estimate vehicle sideslip using tyre force measurements. Most of the vehicle sideslip estimators do not use tyre force measurements and are based on tyre force model. Because of the tyre force model nonlinearities and uncertainties, the estimator accuracy depends highly on factors such as tyre-road friction, vertical load, temperature, tyre pressure, etc. Therefore availability of tyre force measurements offers benefits in vehicle sideslip estimation. The proposed estimator also has advantage over accelerometer based estimators as the later can have estimation errors from roll and pitch dynamics. The estimator is studied in a multi-body vehicle simulator for various maneuvers.