O presente trabalho otimizou os parâmetros concentrados do sistema de suspensão de um modelo de veículo completo, representando um automóvel de passeio que trafega a uma velocidade constante por um determinado perfil de pista previsto na norma ISO 8608, 1995, através da utilização de um algoritmo meta-heurístico de otimização multiobjetivo. Duas rotinas numérico-computacionais foram desenvolvidas, visando realizar tal otimização tanto no domínio do tempo quanto no domínio da frequência. A utilização de algoritmos meta-heurísticos vem ganhando espaço na otimização de sistemas mecânicos, proporcionando rapidez e precisão na obtenção de resultados ótimos. Ao se combinar um algoritmo de otimização a um modelo que represente satisfatoriamente um sistema mecânico, obtém-se uma ferramenta indicadora dos parâmetros de máxima eficiência do sistema, que pode ser utilizada em inúmeras aplicações. Pretendeu-se, com a integração de rotinas de análise dinâmica nos domínios do tempo e da frequência ao algoritmo genético de otimização multiobjetivo NSGA-II, desenvolvido por Deb et al., 2002, a obtenção de duas fronteiras ótimas de Pareto. Estas fronteiras consistem no conjunto de soluções não dominadas que minimizam as seguintes funções objetivo: o valor RMS ponderado da aceleração vertical do assento do motorista, o valor RMS da média do fator de amplificação dinâmica das quatro rodas do modelo e o máximo deslocamento relativo entre cada roda e a carroceria. O método proposto por Shinozuka e Jan, 1972, é utilizado para a obtenção do perfil de irregularidades da pista no domínio do tempo a partir das equações de densidade espectral de potência (PSD) que representam as diferentes classes de pavimentos. O método de Newmark, 1959, é utilizado para resolver a equação diferencial de movimento no domínio do tempo e obter a resposta dinâmica do modelo a tais irregularidades. O comportamento dinâmico do modelo de veículo no domínio da frequência foi obtido através da utilização da função de resposta em frequência (FRF) do modelo de veículo analisado. Os resultados demonstraram a capacidade de ambas as rotinas de análise dinâmica desenvolvidas de produzir resultados consistentes com os encontrados na literatura, bem como a capacidade dos algoritmos de otimização implementados de fornecer fronteiras ótimas de Pareto para os problemas propostos. / The proposed work optimized the concentrated parameters of a full-vehicle model’s suspension system, being that model representative of a passenger car which travels at a constant speed on a certain road profile provided by the ISO 8608, 1995, standard, using a multi-objective meta-heuristic optimization algorithm. Two numerical-computational routines were developed, seeking to perform said optimization for both the time and frequency domains. The use of meta-heuristic algorithms has been increasing in mechanical systems optimization, providing speed and accuracy in obtaining an optimal result. Combining an optimization algorithm with a model that satisfactorily represents a mechanical system yields a tool that indicates the system’s maximum efficiency parameters, which can be used in numerous applications. It was intended, with the integration of the dynamic analysis routines to the multi-objective genetic optimization algorithm NSGA-II, developed by Deb et al., 2002, the obtainment of two Pareto-optimal fronts. These fronts consist in the set of non-dominated solutions that minimize the following objective functions: the weighted RMS value of the driver’s seat vertical acceleration, the mean RMS value of the model wheel’s dynamic amplification factor, and the maximum relative displacement between each wheel and the body of the vehicle model. The method proposed by Shinozuka and Jan, 1972, is used to obtain the road irregularity profile in the time domain from the power spectral density (PSD) equations that represent the different pavement classes. The Newmark’s method (1959) is used to solve the differential motion equation in the time domain, in order to obtain the vehicle model’s responses to these irregularities. The dynamic behavior of the vehicle model in the frequency domain was obtained through the use of the frequency response function (FRF) of the analyzed model. The results showed the capacity of both the dynamic analysis routines developed in generating results that are consistent with those found in literature, as well as the capacity of the optimization algorithms implemented in providing Pareto optimal fronts to the proposed problems.

Cette thèse traite de modélisation des systèmes complexes. Dans ce cadre, l'approche est basée sur les Modèles Structurés en Second Ordre (MSSO). Afin d'utiliser cette classe de modèles, les propriétés telles que l'atteignabilité, l'observabilité et les grammiens, bien connues pour les réalisations d'états, sont étendues aux MSSO.Lors de la co-simulation d'un système, des éléments de natures différentes (physiques et logicielles) sont intégrés et la simulation est effectuée en temps réel. Or, les modèles d'ordre élevés sont couteux en temps de calcul, ce qui rend difficile ce type de simulation. Ainsi, des méthodes de réduction de modèle sont explorées. En particulier, de nouvelles méthodes, permettant de préserver la structure des modèles avec une bonne erreur d'approximation sont présentées.Ces développements sont appliqués à la co-simulation de modèles véhicules sous forme de MSSO. Le modèle créé est un modèle par blocs, complexe et non-linéaire. Afin d'appliquer les méthodes de réduction de modèle il est nécessaire de le linéariser. La structure par blocs permet de linéariser l'ensemble du modèle ou de ne linéariser que certaines sous parties du modèle.Ensuite, l'identification des paramètres est effectuée pour chaque sous-systèmes du véhicule. Une méthode d'interconnexion est ensuite proposée pour créer une représentation monobloc du modèle afin de réduire ce dernier. Au final, des essais en co-simulation de la partie arrière du véhicule sous forme de modèle interconnectée avec la partie avant du véhicule physiquement présente sur un banc de test, valide notre approche pour effectuer de la co-simulation temps réel avec matériel.x / This thesis studies the modeling of complex systems. In this framework, the approach is based on Second Order Form Model (SOFM). In order to use this kind of models, properties such as the reachability, the observability, the gramians and the Markov parameters, well known for state-space representation, are extended to the SOFM. During the co-simulation of a system, its physical parts are interconnected to models which simulate the system environement and the simulation is performed in real time. However, the simulation of high order models consumes to much time to be performed in real time. Therefore, model order reduction methods are studied. Particularly, new methods preserving SOFM structure with a good approximation error are presented. These developments are applied to the vehicle dynamic. Hence, a vehicle SOFM model is developed. The created model is a blockwise model where each blocks describes a part of the vehicle. This model is complex and non-linear. In order to apply the model order reduction methods, model linearisation is necessary. The block modeling allows to linearise the full model or allows to linearise some part of the model. Then, the identification of the model parameters is done by vehicle sub-system. In addition, an interconnection method is proposed to build a monobloc model in order to reduce it. Finally, co-simulations of the model vehicle rear part interconnected to the physical front part of the vehicle show the capacity to make co-simulation with the reduced models.

Le véhicule est un système dynamique complexe, composé de différents sous-systèmes de nature différente (moteur, système de freinage, suspension ...). Chaque sous-système est décrit par un modèle mathématique dépendant d’un nombre important de paramètres, très souvent incertains (méconnaissance, manque de mesures,…). L’incertitude sur les paramètres se propage à travers le modèle et se retrouve sur la sortie. Cette dernière représente les forces et moments mis en jeu dans le véhicule. L’incertitude sur la sortie n’est pas toujours tolérable pour des raisons de sécurité, précision,…Situé dans ce contexte, les travaux de la thèse consistent à proposer des méthodes d’analyse de sensibilité permettant de déterminer les paramètres dont les incertitudes ont un effet significatif sur le comportement d’un système donné, en particulier le véhicule. Dans une première partie, le cas des modèles à paramètres dépendants et suivant une distribution arbitraire est étudié. Une méthode, basée sur la décorrélation des paramètres par la décomposition de Cholesky, a été proposée. Pour résoudre le problème de la distribution arbitraire, l’approximation par polynôme du chaos arbitraire est adoptée, en construisant une base orthonormale en termes de moments statistiques non centrés des paramètres. Les indices de sensibilité, permettant de quantifier la contribution de chaque paramètre à la variance de la sortie, sont obtenus directement à partir des coefficients des polynômes du chaos ainsi obtenus. La méthode proposée est appliquée et validée sur un modèle de pneumatique. Dans la deuxième partie, le cas des modèles dynamiques est traité. Une méthode basée sur les dérivées partielles est explorée, puis une approche alternative est proposée. Elle utilise de façon originale des outils de l’Automatique, les grammiens d’atteignabilité et d’observabilité. L’influence des paramètres sur l’énergie consommée en entrée et restituée par le système en sortie est ainsi déterminée. L’avantage de cette technique est que les paramètres peuvent être classifiés selon leurs influences sur l’énergie consommée ou restituée, tout au long de la dynamique du système. D’autre part, l’étude de la sensibilité des paramètres sur les échanges de l’énergie, permet de déterminer un placement optimal des paramètres pour une optimisation de l’énergie consommée et restituée en sortie. Les deux méthodes proposées sont appliquées et validées sur un modèle bicyclette décrivant le comportement dynamique d’un véhicule. Dans la dernière partie, des tests sur véhicule d’essais ont été réalisés sur circuit. Les différentes approches d’analyse de sensibilité ont été appliquées sur les résultats d’essais, afin de recaler des modèles de pneumatique. / The vehicle is a complex dynamic system, composed of various subsystems of different kind (engine, braking system, suspension, etc.). Each subsystem is described by a mathematical model depending on a significant number of parameters, very often uncertain (unknown, lack of measures, etc.). The uncertainty on the parameters is propagated through the model and takes place on the model output. The model output represents the forces and moments involved in the vehicle. The uncertainty on the model output is not always tolerable for safety reasons, precision, etc. In this context, the aim of the thesis is to propose sensitivity analysis methods allowing to determine parameters whose uncertainties have a significant effect on the behavior of a given system. In the first part, the case of models with dependent parameters which follow an arbitrary distribution is studied. A method based on the decorrelation of the parameters using the decomposition of Cholesky, is proposed. To solve the problem of the arbitrary distribution, an approximation using arbitrary polynomial chaos is adopted and an orthonormal data basis is constructed in terms of non central statistical moments of parameters. Sensitivity indices, allowing to quantify the contribution of every parameter to the model output variance, is directly obtained from the polynomial chaos coefficients.The proposed method is applied and validated on a tyre model. In the second part, the case of the dynamic models is studied. A method based on partial derivative is explored. Then a new alternative approach is proposed. This method uses in an original way the control theory tools, the reachability and observability Gramians. The influence of the parameters is formulated in terms the energy consumed and restored by the system. The advantage of this technique is that the parameters can be classified according to their influences on the consumed or restored energy throughout the system dynamics. On the other hand, the study of the parameters sensitivity based on ratio energy exchanged, allows to determine an optimal placement of the parameters for an optimization of consumed and/or restored energy. Both proposed methods are applied and validated using bicycle model describing vehicle dynamic behavior. Finally, the various sensitivity approaches are applied to adjust tyre model parameters using vehicle measurements acquired during a steady-state maneuver.

In this dissertation, a group of vehicle dynamics simulation tools is developed with two primary goals: to accurately represent vehicle behavior and to provide insight that improves the understanding of vehicle performance. Three tools are developed that focus on tire modeling, vehicle modeling and lap time simulation. Tire modeling is based on Nondimensional Tire Theory, which is extended to provide a flexible model structure that allows arbitrary inputs to be included. For example, rim width is incorporated as a continuous variable in addition to vertical load, inclination angle and inflation pressure. Model order is determined statistically and only significant effects are included. The fitting process is shown to provide satisfactory fits while fit parameters clearly demonstrate characteristic behavior of the tire. To represent the behavior of a complete vehicle, a Nondimensional Tire Model is used, along with a three degree of freedom vehicle model, to create Milliken Moment Diagrams (MMD) at different speeds, longitudinal accelerations, and under various yaw rate conditions. In addition to the normal utility of MMDs for understanding vehicle performance, they are used to develop Limit Acceleration Surfaces that represent the longitudinal, lateral and yaw acceleration limits of the vehicle. Quasi-transient lap time simulation is developed that simulates the performance of a vehicle on a predetermined path based on the Limit Acceleration Surfaces described above. The method improves on the quasi-static simulation method by representing yaw dynamics and indicating the vehicle's stability and controllability over the lap. These improvements are accomplished while maintaining the simplicity and computational efficiency of the two degree of freedom method. / Graduation date: 2013

Active safety systems for road vehicles have been improved considerably in recent years along with technological advances and the increasing demand for road safety. In the development route of active safety systems which started with introduction of digital controlled ABS in the late seventies, vehicle stability control systems have been developed which today, with an integration approach, incorporate ABS and other previously developed active safety technologies. ABS, as a main part of this new structure, still maintains its importance. In this thesis, a design methodology of an antilock braking system controller for four wheeled road vehicles is presented with a detailed simulation work. In the study, it is intended to follow a flexible approach for integration with unified control structure of an integrated active safety system. The objective of the ABS controller, as in the previous designs in literature, is basically to provide retention of vehicle directional control capability and if possible shorter braking distances by controlling the wheel slip during braking. iv A hierarchical structure was adopted for the ABS controller design. A high-level controller, through vehicle longitudinal acceleration based estimation, determines reference slip values and a low-level controller attempts to track these reference slip signals by modulating braking torques. Two control alternatives were offered for the design of the low-level controller: Fuzzy Logic Control and PID Control. Performance of the ABS controller was analyzed through extensive simulations conducted in MATLAB/Simulink for different road conditions and steering maneuvers. For simulations, an 8 DOF vehicle model was constructed with nonlinear tires.

Active safety systems for road vehicles make a crucial preventive contribution to road safety. In recent years, technological developments and the increasing demand for road safety have resulted in the integration and cooperation of these individual active safety systems. Traction control system (TCS) is one of these individual systems, which is capable of inhibiting wheel-spin during acceleration of the vehicle on slippery surfaces. In this thesis, design methodology and simulation results of a traction control system for four wheeled road vehicles are presented. The objective of the TCS controller is basically to improve directional stability, steer-ability and acceleration performance of vehicle by controlling the wheel slip during acceleration. In this study, the designed traction control system based on fuzzy logic is composed of an engine torque controller and a slip controller. Reference wheel slip values were estimated from the longitudinal acceleration data of the vehicle. Engine torque controller determines the throttle opening angle corresponding to the desired wheel torque, which is determined by a slip controller to track the reference slip signals. The wheel torques delivered by the engine are compensated by brake torques according to the desired wheel torque determined by the slip controller. Performance of the TCS controller was analyzed through several simulations held in MATLAB/Simulink for different road conditions during straight line acceleration and combined acceleration and steering. For simulations, an 8 DOF nonlinear vehicle model with nonlinear tires and a 2 DOF nonlinear engine model were built.

This dissertation describes two distinctive methods for human-vehicle interaction recognition: one for ground level videos and the other for aerial videos. For ground level videos, this dissertation presents a novel methodology which is able to estimate a detailed status of a scene involving multiple humans and vehicles. The system tracks their configuration even when they are performing complex interactions with severe occlusion such as when four persons are exiting a car together. The motivation is to identify the 3-D states of vehicles (e.g. status of doors), their relations with persons, which is necessary to analyze complex human-vehicle interactions (e.g. breaking into or stealing a vehicle), and the motion of humans and car doors to detect atomic human-vehicle interactions. A probabilistic algorithm has been designed to track humans and analyze their dynamic relationships with vehicles using a dynamic context. We have focused on two ideas. One is that many simple events can be detected based on a low-level analysis, and these detected events must contextually meet with human/vehicle status tracking results. The other is that the motion clue interferes with states in the current and future frames, and analyzing the motion is critical to detect such simple events. Our approach updates the probability of a person (or a vehicle) having a particular state based on these basic observed events. The probabilistic inference is made for the tracking process to match event-based evidence and motion-based evidence. For aerial videos, the object resolution is low, the visual cues are vague, and the detection and tracking of objects is less reliable as a consequence. Any method that requires accurate tracking of objects or the exact matching of event definition are better avoided. To address these issues, we present a temporal logic based approach which does not require training from event examples. At the low-level, we employ dynamic programming to perform fast model fitting between the tracked vehicle and the rendered 3-D vehicle models. At the semantic-level, given the localized event region of interest (ROI), we verify the time series of human-vehicle relationships with the pre-specified event definitions in a piecewise fashion. With special interest in recognizing a person getting into and out of a vehicle, we have tested our method on a subset of the VIRAT Aerial Video dataset and achieved superior results. / text

O presente trabalho otimizou os parâmetros concentrados do sistema de suspensão de um modelo de veículo completo, representando um automóvel de passeio que trafega a uma velocidade constante por um determinado perfil de pista previsto na norma ISO 8608, 1995, através da utilização de um algoritmo meta-heurístico de otimização multiobjetivo. Duas rotinas numérico-computacionais foram desenvolvidas, visando realizar tal otimização tanto no domínio do tempo quanto no domínio da frequência. A utilização de algoritmos meta-heurísticos vem ganhando espaço na otimização de sistemas mecânicos, proporcionando rapidez e precisão na obtenção de resultados ótimos. Ao se combinar um algoritmo de otimização a um modelo que represente satisfatoriamente um sistema mecânico, obtém-se uma ferramenta indicadora dos parâmetros de máxima eficiência do sistema, que pode ser utilizada em inúmeras aplicações. Pretendeu-se, com a integração de rotinas de análise dinâmica nos domínios do tempo e da frequência ao algoritmo genético de otimização multiobjetivo NSGA-II, desenvolvido por Deb et al., 2002, a obtenção de duas fronteiras ótimas de Pareto. Estas fronteiras consistem no conjunto de soluções não dominadas que minimizam as seguintes funções objetivo: o valor RMS ponderado da aceleração vertical do assento do motorista, o valor RMS da média do fator de amplificação dinâmica das quatro rodas do modelo e o máximo deslocamento relativo entre cada roda e a carroceria. O método proposto por Shinozuka e Jan, 1972, é utilizado para a obtenção do perfil de irregularidades da pista no domínio do tempo a partir das equações de densidade espectral de potência (PSD) que representam as diferentes classes de pavimentos. O método de Newmark, 1959, é utilizado para resolver a equação diferencial de movimento no domínio do tempo e obter a resposta dinâmica do modelo a tais irregularidades. O comportamento dinâmico do modelo de veículo no domínio da frequência foi obtido através da utilização da função de resposta em frequência (FRF) do modelo de veículo analisado. Os resultados demonstraram a capacidade de ambas as rotinas de análise dinâmica desenvolvidas de produzir resultados consistentes com os encontrados na literatura, bem como a capacidade dos algoritmos de otimização implementados de fornecer fronteiras ótimas de Pareto para os problemas propostos. / The proposed work optimized the concentrated parameters of a full-vehicle model’s suspension system, being that model representative of a passenger car which travels at a constant speed on a certain road profile provided by the ISO 8608, 1995, standard, using a multi-objective meta-heuristic optimization algorithm. Two numerical-computational routines were developed, seeking to perform said optimization for both the time and frequency domains. The use of meta-heuristic algorithms has been increasing in mechanical systems optimization, providing speed and accuracy in obtaining an optimal result. Combining an optimization algorithm with a model that satisfactorily represents a mechanical system yields a tool that indicates the system’s maximum efficiency parameters, which can be used in numerous applications. It was intended, with the integration of the dynamic analysis routines to the multi-objective genetic optimization algorithm NSGA-II, developed by Deb et al., 2002, the obtainment of two Pareto-optimal fronts. These fronts consist in the set of non-dominated solutions that minimize the following objective functions: the weighted RMS value of the driver’s seat vertical acceleration, the mean RMS value of the model wheel’s dynamic amplification factor, and the maximum relative displacement between each wheel and the body of the vehicle model. The method proposed by Shinozuka and Jan, 1972, is used to obtain the road irregularity profile in the time domain from the power spectral density (PSD) equations that represent the different pavement classes. The Newmark’s method (1959) is used to solve the differential motion equation in the time domain, in order to obtain the vehicle model’s responses to these irregularities. The dynamic behavior of the vehicle model in the frequency domain was obtained through the use of the frequency response function (FRF) of the analyzed model. The results showed the capacity of both the dynamic analysis routines developed in generating results that are consistent with those found in literature, as well as the capacity of the optimization algorithms implemented in providing Pareto optimal fronts to the proposed problems.

O presente trabalho otimizou os parâmetros concentrados do sistema de suspensão de um modelo de veículo completo, representando um automóvel de passeio que trafega a uma velocidade constante por um determinado perfil de pista previsto na norma ISO 8608, 1995, através da utilização de um algoritmo meta-heurístico de otimização multiobjetivo. Duas rotinas numérico-computacionais foram desenvolvidas, visando realizar tal otimização tanto no domínio do tempo quanto no domínio da frequência. A utilização de algoritmos meta-heurísticos vem ganhando espaço na otimização de sistemas mecânicos, proporcionando rapidez e precisão na obtenção de resultados ótimos. Ao se combinar um algoritmo de otimização a um modelo que represente satisfatoriamente um sistema mecânico, obtém-se uma ferramenta indicadora dos parâmetros de máxima eficiência do sistema, que pode ser utilizada em inúmeras aplicações. Pretendeu-se, com a integração de rotinas de análise dinâmica nos domínios do tempo e da frequência ao algoritmo genético de otimização multiobjetivo NSGA-II, desenvolvido por Deb et al., 2002, a obtenção de duas fronteiras ótimas de Pareto. Estas fronteiras consistem no conjunto de soluções não dominadas que minimizam as seguintes funções objetivo: o valor RMS ponderado da aceleração vertical do assento do motorista, o valor RMS da média do fator de amplificação dinâmica das quatro rodas do modelo e o máximo deslocamento relativo entre cada roda e a carroceria. O método proposto por Shinozuka e Jan, 1972, é utilizado para a obtenção do perfil de irregularidades da pista no domínio do tempo a partir das equações de densidade espectral de potência (PSD) que representam as diferentes classes de pavimentos. O método de Newmark, 1959, é utilizado para resolver a equação diferencial de movimento no domínio do tempo e obter a resposta dinâmica do modelo a tais irregularidades. O comportamento dinâmico do modelo de veículo no domínio da frequência foi obtido através da utilização da função de resposta em frequência (FRF) do modelo de veículo analisado. Os resultados demonstraram a capacidade de ambas as rotinas de análise dinâmica desenvolvidas de produzir resultados consistentes com os encontrados na literatura, bem como a capacidade dos algoritmos de otimização implementados de fornecer fronteiras ótimas de Pareto para os problemas propostos. / The proposed work optimized the concentrated parameters of a full-vehicle model’s suspension system, being that model representative of a passenger car which travels at a constant speed on a certain road profile provided by the ISO 8608, 1995, standard, using a multi-objective meta-heuristic optimization algorithm. Two numerical-computational routines were developed, seeking to perform said optimization for both the time and frequency domains. The use of meta-heuristic algorithms has been increasing in mechanical systems optimization, providing speed and accuracy in obtaining an optimal result. Combining an optimization algorithm with a model that satisfactorily represents a mechanical system yields a tool that indicates the system’s maximum efficiency parameters, which can be used in numerous applications. It was intended, with the integration of the dynamic analysis routines to the multi-objective genetic optimization algorithm NSGA-II, developed by Deb et al., 2002, the obtainment of two Pareto-optimal fronts. These fronts consist in the set of non-dominated solutions that minimize the following objective functions: the weighted RMS value of the driver’s seat vertical acceleration, the mean RMS value of the model wheel’s dynamic amplification factor, and the maximum relative displacement between each wheel and the body of the vehicle model. The method proposed by Shinozuka and Jan, 1972, is used to obtain the road irregularity profile in the time domain from the power spectral density (PSD) equations that represent the different pavement classes. The Newmark’s method (1959) is used to solve the differential motion equation in the time domain, in order to obtain the vehicle model’s responses to these irregularities. The dynamic behavior of the vehicle model in the frequency domain was obtained through the use of the frequency response function (FRF) of the analyzed model. The results showed the capacity of both the dynamic analysis routines developed in generating results that are consistent with those found in literature, as well as the capacity of the optimization algorithms implemented in providing Pareto optimal fronts to the proposed problems.

The Master's thesis deals with the simulations kinematics and dynamics of experimental four-wheeled vehicle with all-wheel steering and all-wheel drive. Suggestion of vehicle stability systems ABS/ASR for traction control is included. There are several dynamics models with their comparison. The estimation of important vehicle parameters is implemented. Based on knowledge the simple vehicle stability system ABS/ASR is created.