Sensor Fault Detection and Fault-Tolerant Estimation of Vehicle States

Manufacturing smarter and more reliable vehicles is a progressing trend in the automotive industry. Many of today’s vehicles are equipped with driver assistant, automated driving and advanced stability control systems. These systems rely on measured or estimated information to accomplish their tasks. Evidently, reliability of the sensory measurements and the estimate information is essential for desirable operation of advanced vehicle subsystems. This thesis proposes a novel methodology to detect vehicle sensor faults, reconstruct the faulty sensory signals and deliver fault-tolerant estimation of vehicle states. The proposed method can detect failures of the longitudinal, lateral and vertical acceleration sensors, roll rate, yaw rate and pitch rate sensors, steering angle sensor, suspension height sensors, and motor torque sensors. The proposed structure can deliver fault-tolerant estimations of the vehicle states including the longitudinal, lateral and vertical tire forces, longitudinal and lateral velocities, roll angle, and pitch angle. Road grade and bank angles are also estimated in this method even in presence of sensor faults. The unified structure in this thesis is realized by fusion of analytical redundancy relations, fault detection observers and adaptive state estimation algorithms. The proposed method can isolate the faults for vehicle stability and control systems and deliver accurate estimation of vehicle states required by such systems despite sensor failures. The methods developed in this thesis are validated through experiments and can operate reliably in various driving scenarios

Vehicle stability controller based on model predictive control

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2020.Os Sistemas Avançados de Assistência ao Motorista (ADAS) são dispositivos automotivos desenvolvidas para auxiliar o motorista na condução, com intuito de melhorar o desempenho dos veículos em diversos aspectos, incluindo segurança. Do ponto de vista da dinâmica veicular, segurança diz respeito a como o veículo responde aos comandos do motorista em manobras arriscadas. A melhoria de manobrabilidade em situações críticas pode ser obtida pela inclusão de controladores eletrônicos de estabilidade (ESCs). Os ESCs são ADAS desenvolvidos para evitar que o motorista perca o controle do veículo. Uma estratégia de atuação utilizada em ESCs é o controle dos torques transferidso para as rodas, de forma que seja aplicado no eixo de guinada um momento estabilizador resultante da diferença entre as forças geradas nos pneus. Essa estratégia é denominada controle direto do momento de guinada (DYC). O ESCs que utilizam DYC podem ser classificados em dois níveis: alto e baixo. O primeiro calcula o momento estabilizador, sem especificar como deve ser feita a distribuição de torque entre as rodas. E o segundo calcula o torque que deve ser transferido para cada roda, por isso é desenvolvido dedicado para o sistema de atuação disponível no veículo. Nessa pesquisa são propostos DYCs de alto e baixo nível baseados em controle preditivo (MPC). O MPC foi escolhido devido às suas capacidades de considerar os limites do sistema de atuação e prever a desestabilização. Porém, a aplicação do MPC em sistemas de controle em tempo real tem como desafio a obtenção de tempos de cálculo compatíveis com a velocidade da dinâmica do processo controlado. Por isso, foram aplicadas parametrizações da for- mulação do MPC que reduzem a sua complecidade computacional. E, para considerar a eficiência computacional na validação dos controladores, os algoritmos propostos foram implementados em ARM Cortex A8 e submetidos a um procedimento de sintonização, que define as configurações ótimas e caracteriza os tempos de cálculo. Simulações model-in-the-loop e hardware-in-the-loop foram realizadas para validação dos controladores. Os resultados dessas simulações mostram que os ESCs são eficazes em evitar a desestabilização da condução, e que os algoritmos possuem efi- ciência computacional para serem eficazes em tempo real, mesmo executando em um hardware de baixo custo. A comparação entre os resultados obtidos com MPC e regulador quadrático linear (LQR) mostrou que é mais vantajoso utilizar o MPC, mesmo seu tempo de cálculo sendo maior. A comparação entre os desempenhos obtidos com diferentes modelos de predição mostrou que, em manobras com maior risco de instabilidade, um melhor desempenho é obtido com o modelo que considera a rolagem, mesmo que insto impacte no aumento do tempo de cálculo. Além disso, dos resultados para veículos com parâmetros diferentes dos valores nominais assumidos na configuração dos controladores, observou-se que os ESCs são sensíveis ao descasamento entre planta e modelo, de forma que não são comprometidas suas eficácias em evitar que o motorista perca o controle do veículoAdvanced Driver Assistance Systems (ADAS) are automotive devices developed to assist the driver, with the aim of improving vehicle performance in several aspects, including safety. From the point of view of vehicle dynamics, safety concerns how the vehicle responds to the driver’s commands in risky maneuvers. The improvement of maneuverability in critical situations can be achieved by the inclusion of electronic stability controllers (ESCs). ESCs are ADAS designed to prevent the driver from losing control of the vehicle. An actuation strategy used in ESCs is to control the torques transferred to the wheels, so that a stabilizing moment resulting from the difference between the forces generated in the tires is applied to the yaw axis. This strategy is called direct yaw moment control (DYC). ESCs using DYC can be classified into two levels: high and low. The first calculates the stabilizing moment, without specifying how to distribute the torque between the wheels. And the second calculates the torque that must be transferred to each wheel, so it is developed dedicated to the actuation system available in the vehicle. In this research, high and low level DYCs based on Model Predctive Control (MPC) are proposed. The MPC was chosen because of its ability to consider the limits of the actuation system and to predict destabilization. However, the application of MPC in real-time control systems has the challenge of obtaining calculation times compatible with the speed of the dynamics of the controlled process. Therefore, parameterizations of the MPC formulation were applied to reduce the computational complexity. And, to consider the computational efficiency in the validation of the controllers, the proposed algorithms were implemented in ARM Cortex A8 and submitted to a tuning procedure, which defines the optimum configurations and characterizes the calculation times. Model-in-the- loop and hardware-in-the-loop simulations were performed to validate the controllers. The results of these simulations show that the ESCs are effective in avoiding the destabilization of driving, and that the algorithms have computational efficiency to be effective in real-time application, even running on low-cost hardware. The comparison between the results obtained with MPC and Linear Quadratic Regulator (LQR) showed that it is more advantageous to use MPC, even though its calculation time is longer. The comparison between the performances obtained with different prediction models showed that, in maneuvers with a higher risk of instability, a better performance is obtained with the model that considers the roll motion, even though it leads to the increase in calculation time. In addition, from the results for vehicles with different parameters from the nominal values assumed in the configuration of the controllers, it was observed that the ESCs are sensitive to the model-plant mismatch , however, their effectiveness in preventing the driver from losing control is maintained

Assessing the Impact of Multi-variate Steering-rate Vehicle Control on Driver Performance in a Simulation Framework

When a driver turns a steering-wheel, he or she normally expects the vehicle\u27s steering system to communicate an equivalent amount of signal to the road-wheels. This relationship is linear and occurs regardless of the steering-wheel\u27s position within its rotational travel. The linear steering paradigm in passenger vehicles has gone largely unchanged since mass production of passenger vehicles began in 1901. However, as more electronically-controlled steering systems appear in conjunction with development of autonomous steering functions in vehicles, an opportunity to advance the existing steering paradigms arises. The following framework takes a human-factors approach toward examining and evaluating alternative steering systems by using Modeling and Simulation methods to track and score human performance. Present conventional steering systems apply a linear relationship between the steering-wheel and the road wheels of a vehicle. The rotational travel of the steering-wheel is 900° and requires two-and-a-half revolutions to travel from end-stop to opposite end-stop. The experimental steering system modeled and employed in this study applies a dynamic curve response to the steering input within a shorter, 225° rotational travel. Accommodation variances, based on vehicle speed and steering-wheel rotational position and acceleration, moderate the apparent steering input to augment a more-practical, effective steering rate. This novel model follows a paradigm supporting the full range of steering-wheel actuation without necessitating hand repositioning or the removal of the driver\u27s hands from the steering-wheel during steering maneuvers. In order to study human performance disparities between novel and conventional steering models, a custom simulator was constructed and programmed to render representative models in a test scenario. Twenty-seven males and twenty-seven females, ranging from the ages of eighteen to sixty-five were tested and scored using the driving simulator that presented two successive driving test vignettes: One vignette using conventional 900° steering with linear response and the other employing the augmented 225° multivariate, non-linear steering. The results from simulator testing suggest that both males and females perform better with the novel system, supporting the hypothesis that drivers of either gender perform better with a system augmented with 225° multivariate, non-linear steering than with a conventional steering system. Further analysis of the simulated-driving scores indicates performance parity between male and female participants, supporting the hypothesis positing no significant difference in driver performance between male and female drivers using the augmented steering system. Finally, composite data from written questionnaires support the hypothesis that drivers will prefer driving the augmented system over conventional steering. These collective findings support justification for testing and refining novel steering systems using Modeling and Simulation methods. As a product of this particular study, a tested and open-sourced simulation framework now exists such that researchers and automotive designers can develop, as well as evaluate their own steering-oriented products within a valid human-factors construct. The open-source nature of this framework implies a commonality by which otherwisedisparate research and development work can be associated. Extending this framework beyond basic investigation to reach applications requiring morespecialized parameters may even impact drivers having special needs. For example, steeringsystem functional characteristics could be comparatively optimized to accommodate individuals afflicted with upper-body deficits or limited use of either or both arms. Moreover, the combined human-factors and open-source approaches distinguish the products of this research as a common and extensible platform by which purposeful automotive-industry improvements can be realized—contrasted with arbitrary improvements that might be brought about predominantly to showcase technological advancements

Advances in Intelligent Vehicle Control

This book is a printed edition of the Special Issue Advances in Intelligent Vehicle Control that was published in the journal Sensors. It presents a collection of eleven papers that covers a range of topics, such as the development of intelligent control algorithms for active safety systems, smart sensors, and intelligent and efficient driving. The contributions presented in these papers can serve as useful tools for researchers who are interested in new vehicle technology and in the improvement of vehicle control systems

Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics 2015

This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: ● Formulations and Numerical Methods ● Efficient Methods and Real-Time Applications ● Flexible Multibody Dynamics ● Contact Dynamics and Constraints ● Multiphysics and Coupled Problems ● Control and Optimization ● Software Development and Computer Technology ● Aerospace and Maritime Applications ● Biomechanics ● Railroad Vehicle Dynamics ● Road Vehicle Dynamics ● Robotics ● Benchmark ProblemsPostprint (published version