Advantages of rear steer in LTI and LPV vehicle stability control

International audienceIn this paper, the advantages of the rear wheel steer in robust yaw stability control of four wheeled vehicles are shown. A MIMO vehicle dynamic stability controller (VDSC) involving front steer, rear steer and rear braking torques is synthesized. The comparison between a vehicle with and without rear steer is done on avoidance maneuver using both LTI and gain-scheduling LPV controller. Both robust Hinf controllers are built by the solution of an LMI problem. To better evaluate the influence of the rear steer on the performance time domain indexes are introduced. The simulation results show that active rear steer enhances vehicle handling on a low friction surface

Engine knock margin control using in-cylinder pressure data: preliminary results

Knock is an undesired phenomenon occurring in spark ignited engines and is controlled acting on the spark timing. This paper presents a closed-loop architecture that makes possible to address the knock control problem with a standard model-based design approach. An engine knock margin estimate is feedback controlled through a PI regulator and its target value is computed starting from the desired knock probability. A black-box modelling approach is used to identify the dynamics between the spark timing and the knock margin and a traditional model-based controller synthesis is performed. Experimental results at the test bench show that, compared to a conventional strategy, the proposed approach allows for a better compromise between the controller speed and the variability of the spark timing. Moreover, another advantage w.r.t. the conventional strategies is that closed-loop performance prove to be constant for different reference probabilities, leading to a more regular engine behaviour

Hazard Detection for Motorcycles via Accelerometers: A Self-Organizing Map Approach

This paper deals with collision and hazard detection for motorcycles via inertial measurements. For this kind of vehicles, the most difficult challenge is to distinguish road's anomalies from real hazards. This is usually done by setting absolute thresholds on the accelerometer measurements. These thresholds are heuristically tuned from expensive crash tests. This empirical method is expensive and not intuitive when the number of signals to deal with grows. We propose a method based on self-organized neural networks that can deal with a large number of inputs from different types of sensors. The method uses accelerometer and gyro measurements. The proposed approach is capable of recognizing dangerous conditions although no crash test is needed for training. The method is tested in a simulation environment; the comparison with a benchmark method shows the advantages of the proposed approach

Friction State Classification Based on Vehicle Inertial Measurements

Tire-road friction is the most important characteristic defining the planar dynamics of wheeled vehicles. It has consequences on the drivability, stability and tuning of the active vehicle dynamics control systems. This paper proposes two online friction estimation methods designed for the adaptation of vehicle dynamics control algorithms. The problem is framed as a classification problem where inertial measurements are used to discriminate between high and low friction regimes. The first method merges a recursive least-squares (RLS) algorithm with a heuristic bistable logic to classify the friction condition and promptly react to its changes. The second method runs a classification algorithm on the slip-acceleration characteristic. Both methods simultaneously account for the longitudinal and lateral dynamics and are tested on experimental data. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

Applying simple PID tuning rules with extended frequency response knowledge

A PID autotuning method is presented to exploit the knowledge of multiple frequency response points while employing simple and well assessed tuning rules (e.g. based on Internal Model Control). This is achieved by selecting, among the available frequency response points, the 'best one' for indices that are compared based on also other points. Hence, the proposed method can ensure for example (local) robustness properties while being just slightly more complex than the single point tuning. Peculiar to the method is the use of the 'contextual' approach, that provides both the controller parameters, and a process model inherently precise near the obtained cutoff frequency. This allows to reliably compute tuning quality indices that require a simulation of the closed loop. The proposed technique can thus assist the user in evaluating the different tunings produced by centering the synthesis on each point. A demonstration of the procedure is given on a set of models taken from a literature benchmark, to witness its usefulness and applicability

Advantages of rear steer in LTI and LPV vehicle stability control

In this paper, the advantages of the rear wheel steer in robust yaw stability control of four wheeled vehicles are shown. A MIMO vehicle dynamic stability controller (VDSC) involving front steer, rear steer and rear braking torques is synthesized. The comparison between a vehicle with and without rear steer is done on avoidance maneuver using both LTI and gain-scheduling LPV controller. Both robust H¥ controllers are built by the solution of an LMI problem. To better evaluate the influence of the rear steer on the performance time domain indexes are introduced. The simulation results show that active rear steer enhances vehicle handling on a low friction surface

Vehicle sideslip estimation: A kinematic based approach

This paper deals with vehicle sideslip angle estimation. The paper introduces an industrially amenable kinematic-based approach that does not need tireâ\u80\u93road friction parameters or other dynamical properties of the vehicle. The convergence of the estimate is improved by the introduction of a heuristic based on readily available inertial measurements. The method is tested on a vast collection of tests performed in different conditions, showing a satisfactory behavior despite not using any information on the road friction. The extensive experimental validation confirms that the estimate is robust to a wide range of driving scenarios

Adaptive and Unconventional Strategies for Engine Knock Control

Knock is an undesirable phenomenon affecting the gasoline spark-ignition (SI) engines. In order to maximize the engine efficiency and output torque while limiting the knock rate, the spark timing should be adequately controlled. This brief focuses on the closed-loop knock control strategies. The proposed control strategies, compared with conventional approaches, show improved performances while remaining simple to use, implement, and tune. First, a deterministic controller that employs a logarithmic increase of the spark timing proves to outperform the conventional strategy in terms of spark timing average and variance. In addition, an adaptive parameter strategy that exploits stochastic information of the process is introduced. Thanks to this extension, the average and the variance of the spark timing are additionally improved while preserving the ease of tuning and the fast reaction times of the deterministic strategy. Throughout this brief, all the knock controllers are compared with a conventional deterministic strategy and with a recently proposed stochastic one. The advantages of the proposed approaches are confirmed both by simulation and by experimental data collected at a test bench

Analysis of a vibrotactile actuator for bicycle handlebars

Vibrotactile systems are convenient solutions for managing interaction between automatic control systems and humans. This paper develops a vibrotactile assistance system (VAS) for high performance bicycles. The system is designed to assist the rider during braking in order to minimize the time to stop, increasing performances and safety. The proposed control architecture is the result of the low cost system requirement and the need to minimize the response time from wheel slip to vibrotactile feedback. A cascade control architecture guarantees the precise control of the excitation frequency and short delays between the front wheel slip and the stimulus to the rider. The controllers are tested on a test bed bike