1,721,017 research outputs found
On the Benefits of Torque Vectoring for Automated Collision Avoidance at the Limits of Handling
Full text linkThis paper presents a novel approach integrating motion replanning, path tracking and vehicle stability for collision avoidance using nonlinear Model Predictive Contouring Control. Employing torque vectoring capabilities, the proposed controller is able to stabilise the vehicle in evasive manoeuvres at the limit of handling. A nonlinear double-track vehicle model, together with an extended Fiala tyre model, is used to capture the nonlinear coupled longitudinal and lateral dynamics. The optimised control inputs are the steering angle and the four longitudinal wheel forces to minimise the tracking error in safe situations and maximise the vehicle-to-obstacle distance in emergency manoeuvres. These optimised longitudinal forces generate an additional direct yaw moment, enhancing the vehicle's lateral agility and aiding in obstacle avoidance and stability maintenance. The longitudinal tyre forces are constrained using the tyre friction cycle. The proposed controller has been tested on rapid prototyping hardware to prove real-time capability. In a high-fidelity simulation environment validated with experimental data, our proposed approach successfully avoids obstacles and maintains vehicle stability. It outperforms two baseline controllers: one without torque vectoring and another one without collision avoidance prioritisation. Furthermore, we demonstrate the robustness of the proposed approach to vehicle parameter variations, road friction, perception, and localisation errors. The influence of each variation is statistically assessed to evaluate its impact on the performance, providing guidelines for future controller design
Motorcycle multibody model validation for HuiL simulator - Results
No full textThis dataset contains the collection of results presented in the article: "Motorcycle multibody model validation for HuiL simulation" by authors: Grottoli, Marco; Celiberti, Francesco; van der Heide, Anne; Lemmens, Yves; Happee, Riender
Time domain force identification: for noise and vibration prediction in vehicles
No full textIn many engineering fields it is beneficial to obtain information about the force acting on a dynamical system. As measurement of this force is often difficult or impossible a technique that identifies this force in an alternative manner is desired. A wide variety of methods is available in literature. Obtaining this force in the frequency domain is done often. However, in certain cases where the input force is non-stationary a frequency domain technique does not suffice. This thesis therefore focuses on obtaining a reliable force identification method in the time domain. The force identification problem can be seen as an ’inverse problem’ to which a simple analytical solution is not trivial. A more advanced method is required. Methods found in literature can be grouped into three categories which fundamentally differ in the way the dynamics is modelled. Deterministic force identification methods are defined as methods where the dynamics is modelled deterministically. Whenever a methods uses a stochastic model it is considered a stochastic force identification method. A third group of force identification methods uses artificial intelligence to obtain a model of the system when no model is available. In this thesis it is assumed a model of the system dynamics is available and therefore artificial intelligence methods for force identification are not considered. Deterministic force identification method including regularization methods, recursive methods and iterative methods are compared to stochastic methods which are all based on the Kalman filter. The most relevant methods are evaluated using simulated data of a single and multiple degree of freedom dynamical system and measured performed on an aluminium structure. It was concluded that the Least Mean Square Adaptive Algorithm outperforms the Joint Input-State Estimator with Artificial Displacement Measurements in identifying forces acting on the simulated single and multiple degree of freedom system as well as the forces acting on the aluminium structure
Design of an adaptive brake pressure controller for the antilock braking system
No full textIn the past few decades, the introduction of electronics in motor vehicles has marked its
development. At the beginning, electronic systems were used to control the engine
(electronic fuel-injection systems). From that time on, electronic components entered the domain of driving safety (e.g. the Anti-lock Braking System, Electronics Stability Control or the Adaptive Cruise Control) up to the point that completely new fields of application have emerged in the areas of driving assistance, communication and infotainment as a result of continuous improvements in semiconductor technology.
This thesis is focused on the second component mentioned, the Anti-lock Braking System (ABS). Specifically, the ABS prevents the wheels from locking when the brakes are
applied by detecting incipient wheel lock on one or more wheels and makes sure that both
lateral and longitudinal friction are optimal by dynamically controlling the brake pressure of individual wheels. By doing so, wheels are prevented from locking up, the braking distance is minimized and the vehicle remains steerable.
The Electronic Control Unit (ECU) contains, among others, the ABS functionality, which
is comprised by two main parts: the high level ABS algorithm and the low level brake
pressure control. The first sends a pressure request signal - determined from complex
control systems based on heuristic rules - to the pressure controller, which has to be
applied on the desired brake pad precisely.
This work is focused on the low level control in order to make it as precise as possible and perform optimally with changing hydraulic system characteristics. By carrying out a wide analysis of response data with the current feed-forward controller structure, its system characteristics and key parameters have been identified. This has been possible thanks to a partnership between TU Delft and SKF, from which a BMW 5 series test vehicle has been acquired and modified for any kind of safety control system, such as the installation of active suspension, force sensing bearings or the hereby needed hydraulic ABS circuit modification.
The main outcome of the first part of the work is the definition of a new model which, a part from considering the voltage as a new input for the pressure step estimation,
improves the build up phase accuracy more than a 10% by smoothing the compressibility
effect of the brake fluid.
The second part of the work focuses on the design of an Adaptive Brake Pressure
Controller which is based on an adaptive mapping continuously updated by the Recursive
Least Squares algorithm. The results are quite promising. Indeed, this novel control
system is expected to increase the accuracy of the initial controller more than a 40%
while adapting to the changing-system, thus accomplishing the main objectives of this
work. Furthermore, the smaller pressure steps, the main drawback of the previous feedback controller, are presumably going to be accurately reached.
Last section of this chapter suggests different methodologies to determine the quality of the new designed adaptive control system which, if proved to be successful, would be a great step in the development of this important active safety control system which is the Anti-lock Braking System.Outgoin
Design of an adaptive brake pressure controller for the antilock braking system
No full textIn the past few decades, the introduction of electronics in motor vehicles has marked its
development. At the beginning, electronic systems were used to control the engine
(electronic fuel-injection systems). From that time on, electronic components entered the domain of driving safety (e.g. the Anti-lock Braking System, Electronics Stability Control or the Adaptive Cruise Control) up to the point that completely new fields of application have emerged in the areas of driving assistance, communication and infotainment as a result of continuous improvements in semiconductor technology.
This thesis is focused on the second component mentioned, the Anti-lock Braking System (ABS). Specifically, the ABS prevents the wheels from locking when the brakes are
applied by detecting incipient wheel lock on one or more wheels and makes sure that both
lateral and longitudinal friction are optimal by dynamically controlling the brake pressure of individual wheels. By doing so, wheels are prevented from locking up, the braking distance is minimized and the vehicle remains steerable.
The Electronic Control Unit (ECU) contains, among others, the ABS functionality, which
is comprised by two main parts: the high level ABS algorithm and the low level brake
pressure control. The first sends a pressure request signal - determined from complex
control systems based on heuristic rules - to the pressure controller, which has to be
applied on the desired brake pad precisely.
This work is focused on the low level control in order to make it as precise as possible and perform optimally with changing hydraulic system characteristics. By carrying out a wide analysis of response data with the current feed-forward controller structure, its system characteristics and key parameters have been identified. This has been possible thanks to a partnership between TU Delft and SKF, from which a BMW 5 series test vehicle has been acquired and modified for any kind of safety control system, such as the installation of active suspension, force sensing bearings or the hereby needed hydraulic ABS circuit modification.
The main outcome of the first part of the work is the definition of a new model which, a part from considering the voltage as a new input for the pressure step estimation,
improves the build up phase accuracy more than a 10% by smoothing the compressibility
effect of the brake fluid.
The second part of the work focuses on the design of an Adaptive Brake Pressure
Controller which is based on an adaptive mapping continuously updated by the Recursive
Least Squares algorithm. The results are quite promising. Indeed, this novel control
system is expected to increase the accuracy of the initial controller more than a 40%
while adapting to the changing-system, thus accomplishing the main objectives of this
work. Furthermore, the smaller pressure steps, the main drawback of the previous feedback controller, are presumably going to be accurately reached.
Last section of this chapter suggests different methodologies to determine the quality of the new designed adaptive control system which, if proved to be successful, would be a great step in the development of this important active safety control system which is the Anti-lock Braking System.Outgoin
Conception and development of an interaction framework for a collaborative assistance vehicle
No full textRepresenting the Car-Following Behaviour of Adaptive Cruise Control (ACC) Systems Using Parametric Car-Following Models
No full textThe Dutch governmental organisation Rijkswaterstaat contributes to the smooth and safe flow of traffic, as both traffic jams and accidents cost society large amounts of money each day. Roads are designed for the current traffic composition. Due to the promotion of Adaptive Cruise Control (ACC) systems, utilisation of these systems is expected to increase. Society benefits from insights into the effects these systems have on traffic flow, as they can help to reduce traffic jams and accidents. ACC systems are designed to increase driving comfort by taking over throttling and braking from the human driver. For optimal driver acceptance, these systems show similar driving behaviour to that of human drivers. However, this is not entirely possible due to limited anticipation. To predict how differences in driving behaviour affect traffic flows, researchers usually perform simulations using parametric car-following models. However, research shows contradictory findings. The goal of this research was to gain insights into the performance of commonly applied parametric car-following models on representing the driving behaviour of ACC systems. Optimal model calibration was obtained by investigating the sensitivity of the model calibration to synthetic data. Investigated were the calibration methodology and the quality and quantity of calibration data. Models are calibrated to real-world driving data from an Audi A4 from 2017. These models were used to assess the capability of representing typical highway scenarios: steady-state car-following, cut-in, cut-out, hard-braking and stop-and-go scenarios. The considered models were the Intelligent Driver Model (IDM) model, which has previously been applied to model the driving behaviour of human drivers, the newly developed simplified ACC (sACC) model and a variant on this model. Insights in the sensitivity of the model calibration were obtained by performing a sensitivity analysis on synthetic data. Essential factors in achieving an optimal model calibration are: 1) the model closely matches the driving behaviour in the data, 2) noise levels are as low as possible and 3) the data should contain as many situations as possible that are also included in the model. The dataset must be sufficiently long to include all these situations and to allow the model to develop its dynamics entirely. Using these insights, a calibration was performed on real-world ACC driving data from an Audi A4 (2017). For the ACC system, it was found: 1) the ACC system exhibits non-linear driving behaviour, 2) the acceleration depends on the current velocity and distance to the desired velocity, 3) the system does not consider an intelligent braking strategy and is thus not able of handling safety-critical driving situations and 4) the model includes a sub-controller which ensures comfortable driving behaviour. Except for the comfortable sub-controller, the non-linear IDM model considers all of these factors and thus best represents the driving behaviour. The linear sACC model cannot represent standing conditions, which is resolved in the alternative version. The linearity allows for a better representation of the behaviour of the comfortable sub-controller. However, it disallows for an accurate representation of the dynamics by the models.Mechanical Engineerin
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