Development of fuzzy anti-roll bar controller for improving vehicle stability

The main objective of this paper is to develop active control mechanism based on fuzzy logic controller (FLC) for improving vehicle path following, roll and handling performances simultaneously. At the first stage, 3DOF vehicle model which includes yaw rate, lateral velocity (lateral dynamic) and roll angle (roll dynamic) are developed. The controller produces optimal moment to increase stability and roll margin of vehicle by receiving the steering angle as an input and vehicle variables as a feedback signal. The effectiveness of proposed controller and vehicle model are evaluated during fishhook and single lane-change maneuvers. Simulation results demonstrate that FLC by reducing roll angle, lateral velocity and acceleration, vehicle roll resistance and handling properties are improved. Finally the sensitivity and robustness analysis of developed controller for varying longitudinal speeds are investigated

A Review of Active Yaw Control System for Vehicle Handling and Stability Enhancement

Yaw stability control systemplays a significant role in vehicle lateral dynamics in order to improve the vehicle handling and stability performances. However, not many researches have been focused on the transient performances improvement of vehicle yaw rate and sideslip tracking control. This paper reviews the vital elements for control system design of an active yaw stability control system; the vehicle dynamic models, control objectives, active chassis control, and control strategies with the focus on identifying suitable criteria for improved transient performances. Each element is discussed and compared in terms of their underlying theory, strengths, weaknesses, and applicability. Based on this, we conclude that the sliding mode control with nonlinear sliding surface based on composite nonlinear feedback is a potential control strategy for improving the transient performances of yaw rate and sideslip tracking control

Otimização do comportamento dinâmico lateral e vertical de um ônibus modelado como sistema multicorpo

Existe necessidade de se desenvolver modelos teóricos e testes experimentais, que nos permitam ter plenas condições de melhor avaliar e concluir sobre o comportamento dinâmico dos ônibus, ao trafegar sobre diferentes pistas e realizar diversos tipos de manobras. O objetivo do trabalho é avaliar e otimizar simultaneamente o comportamento dinâmico lateral e vertical de um ônibus modelado como um sistema multicorpo. A metodologia utilizada no trabalho é dividida em duas partes. A primeira parte consiste na programação de um modelo multicorpo de ônibus que possa ser utilizado para fins de otimização do seu comportamento de dinâmica lateral via programação matemática; o desenvolvimento de uma manobra do tipo mudança dupla de faixa - DLC (Double Lane Change), adaptada da combinação da norma ISO 3888-1:1999 que envolve mudança dupla de faixa para carros de passeio e a norma ISO 14791:2000 que envolve mudança simples de faixa para veículos comerciais, na ausência de normas específicas; e finalmente a validação de resultados através de testes experimentais e simulações computacionais. A segunda parte consiste na programação de um modelo multicorpo de ônibus para fins de otimização do seu comportamento de dinâmica vertical via programação matemática, neste caso sujeito a uma pista da classe C segundo classificação da norma ISO 8608:1995. Os resultados específicos da programação das manobras laterais do modelo de ónibus foram validados experimentalmente, bem como comparados através da simulação das manobras num modelo virtual implementado num software multicorpo comercial. O conjunto das soluções atingidas mostraram boa correlação, possibilitando a posterior otimização dos parâmetros concentrados da suspensão do modelo multicorpo de ônibus, através da técnica de algoritmos genéticos. A função objetivo implementada consiste da composição penalizada do valor RMS do ângulo de rolagem da manobra lateral quanto ao handling, e de parâmetros associados ao conforto e segurança, como o valor RMS da aceleração vertical, do deslocamento máximo da suspensão, e da deflexão máxima do pneu de forma a garantir aderência continua à pista. Os resultados otimizados dos parâmetros concentrados conseguem uma negociação dos objetivos conflitantes.There is a need for theoretical models and experimental tests to be developed that allow for better assessments and conclusions about the dynamic behavior of buses driving on different lanes and performing various types of maneuvers. The purpose of this work is to evaluate and optimize both the lateral and the vertical dynamic behavior of a bus modeled as a multibody system. The methodology employed comprises two parts. The first part consists in programming a bus multibody model that can be used to optimize the lateral dynamic behavior of buses via mathematical programming; developing a type of maneuver known as Double Lane Change (DLC), adapted from a combination of the ISO 3888-1:1999 standard, which involves double lane changes for passenger cars, and the ISO 14791:2000 standard, which involves single lane changes for commercial vehicles, in the absence of specific standards; and lastly, validating the results by means of experimental tests and computational simulations. The second part consists in programming a bus multibody model to optimize the vertical dynamic behavior via mathematical programming, in this case for a class C road, according to the classification of the ISO 8608:1995 standard. The specific results of the programming of the lateral maneuvers of the bus model were validated experimentally and then compared with simulations of the maneuvers by a virtual model developed using commercial multibody software. The results showed a good correlation, enabling subsequent optimization of the lumped parameters of the suspension of the bus multibody model using the genetic algorithm optimization technique. The objective function consists of the penalized composition of some terms, including the RMS value of the roll angle of the lateral handling maneuver and of parameters associated with comfort and safety, such as the RMS value of vertical acceleration, the maximum suspension working space, and the maximum tire deflection to ensure continuous adherence on the road surface. The optimized results of the lumped parameters of the suspension enable an alignment of the conflicting goals

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

Modeling and Robust Control of Integrated Ride and Handling of Passenger Cars

Vehicle industries in the last decade have focused on improving ride quality and safety of passenger cars. To achieve this goal, modeling and simulation of dynamic behaviour of vehicles have been widely studied to design model based and robust control strategies. This PhD work presents a new integrated vehicle model and a nonlinear robust controller. The thesis is divided into two main sections: dynamic modeling and controller design. A new fourteen Degrees of Freedom integrated ride and handling vehicle model is proposed using Lagrangian method in terms of quasi-coordinates. The governing equations are derived considering the interaction between the ride and handling systems, Euler motion of the frames attached to the wheels and body, the load transfer among the wheels, acceleration and braking. A non-dimensional factor called coupling factor is introduced to study the coupling among different DOFs of the dynamic system for a defined vehicle maneuver. The coupling factor is considered as an indicator parameter to demonstrate the advantages of the developed model over the existing dynamic models. The improved model is validated using ADAMS/Car for different manoeuvres. The simulation results confirm the accuracy of the improved dynamic model in comparison with the ADAMS/Car simulations and the models available in the literature. Considering the proposed nonlinear integrated ride and handling vehicle model, a nonlinear robust controller is designed for an intermediate passenger car. The H∞ robust control strategy is designed based on the Hamiltonian-Jacobi-Isaacs (HJI) function, Linear Matrix Inequality and State Feedback techniques. In order to improve the ride and handling quality of the vehicle, a Magneto-rheological (MR) damper and a differential braking system are used as control devices. A frequency dependent MR damper model is proposed based on the Spencer MR damper model. The parameters of the model are identified using a combination of Genetic algorithms and Sequential Quadratic Programming approaches based on the experimental data. A mathematical model is validated using the experimental results which confirm the improvement in the accuracy of the model and consistency in the variation of damping with frequency. Based on the proposed MR damper model, an inverse model for the MR damper is designed. A differential braking system is designed to assign desired braking action. The dynamic behavior of the controlled vehicle is simulated for single lane change and bump input, considering three different road conditions: dry, rainy and snowy. The robustness of the designed controller is investigated when the vehicle is under these road conditions. The simulation results confirm the interactive nature of the ride and handling systems and the robustness of the designed control strategy

Vehicle Stability Control Considering the Driver-in-the-Loop

A driver‐in‐the‐loop modeling framework is essential for a full analysis of vehicle stability systems. In theory, knowing the vehicle’s desired path (driver’s intention), the problem is reduced to a standard control system in which one can use different methods to produce a (sub) optimal solution. In practice, however, estimation of a driver’s desired path is a challenging – if not impossible – task. In this thesis, a new formulation of the problem that integrates the driver and the vehicle model is proposed to improve vehicle performance without using additional information from the future intention of the driver. The driver’s handling technique is modeled as a general function of the road preview information as well as the dynamic states of the vehicle. In order to cover a variety of driving styles, the time‐ varying cumulative driver's delay and model uncertainties are included in the formulation. Given that for practical implementations, the driver’s future road preview data is not accessible, this information is modeled as bounded uncertainties. Subsequently, a state feedback controller is designed to counteract the negative effects of a driver’s lag while makes the system robust to modeling and process uncertainties. The vehicle’s performance is improved by redesigning the controller to consider a parameter varying model of the driver‐vehicle system. An LPV controller robust to unknown time‐varying delay is designed and the disturbance attenuation of the closed loop system is estimated. An approach is constructed to identify the time‐varying parameters of the driver model using past driving information. The obtained gains are clustered into several modes and the transition probability of switching between different driving‐styles (modes) is calculated. Based on this analysis, the driver‐vehicle system is modeled as a Markovian jump dynamical system. Moreover, a complementary analysis is performed on the convergence properties of the mode‐dependent controller and a tighter estimation for the maximum level of disturbance rejection of the LPV controller is obtained. In addition, the effect of a driver’s skills in controlling the vehicle while the tires are saturated is analyzed. A guideline for analysis of the nonlinear system performance with consideration to the driver’s skills is suggested. Nonlinear controller design techniques are employed to attenuate the undesirable effects of both model uncertainties and tire saturation