7 research outputs found
Straight running – stability analysis with a driving simulator
No full textThe straight running of the system composed by a car plus driver is studied. Straight running is an important case study for analysing stability. Despite the lateral slip angles of the tyres are small, the system is highly non linear, due essentially to the driver action. Following the simple model of McRuer, later developed by Mistschke and revised by many other authors, we have developed a mathematical model of a car plus driver. The dynamic behaviour of the mathematical model has shown the presence of limit cycles generated by so called Hopf-bifurcations. The mathematical model predicts that, despite the understeering vehicle is globally stable, the driver can make the whole system (car plus driver) unstable. This occurs in case an external disturbance is sufficiently strong. If the external disturbance is small, the understeering vehicle plus driver remains stable. There is a speed above which the understeering car plus driver is unstable, usually such a speed is much greater than the maximum speed of the car on high grip surface. The statements introduced above have been validated by employing the driving simulator of Danisi Engineering, Nichelino, Italy. We experimentally saw that limit cycles do exist and that the driver can make the understeering vehicle model of the simulator quite unstable. We were able to validate the mathematical model by including two humans in the driving loop. One driver was a professional driver, the other one was a novice. The same non linear behaviours were highlighted for the two drivers, however, the amplitudes of the limit cycles and the ability of controlling the car were higher for the professional driver. A question arises whether an electronic power steering (EPS) may reduce or cancel instability. The answer is that there are a number of possible solutions for ESP to counteract the effect of unstable limit cycle
Recurrent Neural Network Model for On-Board Estimation of the Side-Slip Angle in a Four-Wheel Drive and Steering Vehicle
No full textA valuable quantity for analyzing the lateral dynamics of road vehicles is the side-slip angle, that is,
the angle between the vehicle’s longitudinal axis and its speed direction. A reliable real-time side slip angle value enables several features, such as stability controls, identification of understeer and
oversteer conditions, estimation of lateral forces during cornering, or tire grip and wear estimation.
Since the direct measurement of this variable can only be done with complex and expensive devices,
it is worth trying to estimate it through virtual sensors based on mathematical models. This article
illustrates a methodology for real-time on-board estimation of the side-slip angle through a machine
learning model (SSE—side-slip estimator). It exploits a recurrent neural network trained and tested
via on-road experimental data acquisition. In particular, the machine learning model only uses input
signals from a standard road car sensor configuration. The model adaptability to different road
conditions and tire wear levels has been verified through a sensitivity analysis and model testing on
real-world data proves the robustness and accuracy of the proposed solution achieving a root mean
square error (RMSE) of 0.18 deg and a maximum absolute error of 1.52 deg on the test dataset. The
proposed model can be considered as a reliable and cheap potential solution for the real-time
on-board side-slip angle estimation in serial cars
How Drivers Lose Control of the Car
No full textAfter a severe lane change, a wind gust, or another disturbance, the driver might be unable to recover the intended motion. Even though this fact is known by any driver, the scientific investigation and testing on this phenomenon is just at its very beginning, as a literature review, focusing on SAE Mobilus (R) database, reveals. We have used different mathematical models of car and driver for the basic description of car motion after a disturbance. Theoretical topics such as nonlinear dynamics, bifurcations, and global stability analysis had to be tackled. Since accurate mathematical models of drivers are still unavailable, a couple of driving simulators have been used to assess human driving action. Classic unstable motions such as Hopf bifurcations were found. Such bifurcations seem almost disregarded by automotive engineers, but they are very well-known by mathematicians. Other classic unstable motions that have been found are "unstable limit cycles." The driving simulator results have been reproduced by experimental tests on track. We have assessed that the driver's steering action can make the car motion unstable if a proper disturbance has acted. The delay of the driver's steering action is the primary cause for the generation of limit cycles. Future automated vehicles should be conceived by focusing on the addressed phenomenon
Global stability of road vehicle motion with driver control
No full textThe paper contributes to unveil how drivers-either human or not-may lose control of road vehicles after a disturbance. First, a simple vehicle-and-driver model is considered: Its motion is characterized by the existence of limit cycles whose amplitude depend on vehicle forward velocity (both oversteering and understeering vehicles may exibit this property). Such limit cycles are originated by a Hopf bifurcation occurring at a relatively high vehicle forward velocity. A mathematical proof of the existence of Hopf bifurcations is given. The existence of Hopf bifurcations and saddle limit cycles is confirmed by experimental tests performed by a dynamic driving simulator with a complex vehicle model and human in the loop. By a Zubov method, a Lyapunov function is derived to compute the region of asymptotic stability for the simple vehicle-and-driver model. A necessary and sufficient condition is derived for global asymptotic stability. Such a condition refers to the variation of the kinetic energy which must vanish at the end of the disturbed motion. This occurrence has been detected at the driving simulator too. Just a single stable equilibrium has been found inside the domain of attraction in all of the examined cases
Simulazione real time di un cambio dual clutch
No full textLAUREA SPECIALISTICAIl cambio dual clutch Ferrari è stato riprodotto in un modello per eseguire simulazioni real-time in modalità HiL (Hardware-in-the-loop) e SiL (Software-in-the-loop) con driver umano o virtuale. Il modello, comprendente anche differenziale e semiassi, è stato creato e simulato offline all’interno del software MapleSim per una prima validazione e messa a punto delle logiche di controllo. Dopodiché è stato implementato nel modello di veicolo e testato in modalità SiL all’interno dell’ambiente di simulazione CarRealTime. Infine è stato inserito nel modello di driveline (composta da motore e trasmissione) della vettura sviluppato in SimuLink e implementato nel modello di veicolo utilizzato al simulatore nelle modalità HiL. La validità del modello è stata effettuata tramite un confronto tra i dati acquisiti sulle vetture reali e gli output delle simulazioni HiL a parità di input dal driver.The dual clutch trasmission of the Ferrari has been reproduced in a model for real-time simulations with both HiL (Hardware-in-the-loop) and SiL (Software-in-the-loop) approach, with virtual or human drivers. The model, with differential and driveshafts included, has been created and simulated offline with the software MapleSim for a first validation and tuning of the control logics. After that, it has been implemented and tested in the vehicle model in SiL simulations within the simulation environment CarRealTime. Finally, it was inserted in the driveline (composed of engine and transmission) model of the car built in Simulink and implemented in the vehicle model used in the simulator for HiL simulations. The validity of the model was carried out through a comparison between the acquired data on real cars and the output of the HiL simulations for equal inputs from the driver
