Saied Taheri

An adaptive integrated algorithm for active front steering and direct yaw moment control based on direct Lyapunov method

In this article, an adaptive integrated control algorithm based on active front steering and direct yaw moment control using direct Lyapunov method is proposed. Variation of cornering stiffness is considered through adaptation laws in the algorithm to ensure robustness of the integrated controller. A simple two degrees of freedom (DOF) vehicle model is used to develop the control algorithm. To evaluate the control algorithm developed here, a nonlinear eight-DOF vehicle model along with a combined-slip tyre model and a single-point preview driver model are used. Control commands are executed through correction steering angle on front wheels and braking torque applied on one of the four wheels. Simulation of a double lane change manoeuvre using Matlab®/Simulink is used for evaluation of the control algorithm. Simulation results show that the integrated control algorithm can significantly enhance vehicle stability during emergency evasive manoeuvres on various road conditions ranging from dry asphalt to very slippery packed snow road surfaces.

Optimal preview game theory approach to vehicle stability controller design

Dynamic game theory brings together different features that are keys to many situations in control design: optimisation behaviour, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degrees-of-freedom vehicle-handling performance model is put into discrete form to develop the game equations of motion. To evaluate the developed control algorithm, CarSim with its built-in nonlinear vehicle model along with the Pacejka tire model is used. The control algorithm is evaluated for a lane change manoeuvre, and the optimal set of steering angle and corrective yaw moment is calculated and fed to the test vehicle. Simulation results show that the optimal preview control algorithm can significantly reduce lateral velocity, yaw rate, and roll angle, which all contribute to enhancing vehicle stability.

Estimation of tire–road friction coefficient and its application in chassis control systems

Knowledge of tire–road friction conditions is indispensable for many vehicle control systems. In particular, friction information can be used to enhance the performance of wheel slip control systems, for example, knowledge of the current maximum coefficient of friction would allow an anti-lock brake system (ABS) controller to start braking with the optimal brake pressure, meaning the early cycles of operation are more efficient, resulting in shorter stopping distances. Also, from a passive safety perspective, it may be useful to present the driver with friction information so they can adjust their driving style to the road conditions. Hence, it is highly desirable to estimate friction using existing onboard vehicle sensor information. Many approaches for estimating tire–road friction estimation have been proposed in the literature with different sensor requirements and relative excitation levels. This paper aims at estimating the tire–road friction coefficient by using a well-defined model of the tire behavior. The model adopted for this purpose is the physically based brush tire model. In its simplest formulation, the brush model describes the relationship between the tire force and the slip as a function of two parameters, namely, tire stiffness and the tire–road friction coefficient. Knowledge of the shape of the force–slip characteristics of the tire, possibly obtained through the estimation of both friction and tire stiffness using the brush model, provides information about the slip values at which maximum friction is obtained. This information could be used to generate a target slip set point value for controllers, such as an ABS or a traction control system. It is also important to realize that a model-based approach is inherently limited to providing road surface friction information when the tire is exposed to an excitation with high utilization levels (i.e. under high-slip conditions). To be of greatest use to active safety control systems, an estimation method needs to offer earlier knowledge of the limits. In order to achieve the aforementioned objective, an integrated approach using an intelligent tire-based friction estimator and the brush tire model-based estimator is presented. An integrated approach gives us the capability to reliably estimate friction for a wider range of excitations (both low-slip and high-slip conditions).

Enhancement of Collision Mitigation Braking System Performance Through Real-Time Estimation of Tire-road Friction Coefficient by Means of Smart Tires

In the case of modern day vehicle control systems employing a feedback control structure, a real-time estimate of the tire-road contact parameters is invaluable for enhancing the performance of the chassis control systems such as anti-lock braking systems (ABS) and electronic stability control (ESC) systems. However, at present, the commercially available tire monitoring systems are not equipped to sense and transmit high speed dynamic variables used for real-time active safety control systems. Consequently, under the circumstances of sudden changes to the road conditions, the drivers ability to maintain control of the vehicle maybe at risk. In many cases, this requires intervention from the chassis control systems onboard the vehicle. Although these systems perform well in a variety of situations, their performance can be improved if a real-time estimate of the tire-road friction coefficient is available. Existing tire-road friction estimation approaches often require certain levels of vehicle longitudinal and/or lateral motion to satisfy the persistence of excitation condition for reliable estimations. Such excitations may undesirably interfere with vehicle motion controls. This paper presents a novel development and implementation of a real-time tire-road contact parameter estimation methodology using acceleration signals from a smart/intelligent tire. The proposed method characterizes the terrain using the measured frequency response of the tire vibrations and provides the capability to estimate the tire road friction coefficient under extremely lower levels of force utilization. Under higher levels of force excitation (high slip conditions), the increased vibration levels due to the stick/slip phenomenon linked to the tread block vibration modes make the proposed tire vibrations based method unsuitable. Therefore for high slip conditions, a tire-road friction model-based parameter estimation approach is proposed. Hence an integrated approach using the smart/intelligent tire based friction estimator and the model based estimator gives us the capability to reliably estimate friction for a wider range of excitations. Considering the strong interdependence between the operating road surface condition and the instantaneous forces and moments generated; this real time estimate of the tire-road friction coefficient is expected to play a pivotal role in improving the performance of a number of vehicle control systems. In particular, this paper focuses on the possibility of enhancing the performance of collision mitigation braking systems. Language: en

A Modified Dugoff Tire Model for Combined-slip Forces

Abstract Easy-to-use tire models for vehicle dynamics have been persistently studied for such applications as control design and model-based on-line estimation. This paper proposes a modified combined-slip tire model based on Dugoff tire. The proposed model takes emphasis on less time consumption for calculation and uses a minimum set of parameters to express tire forces. Modification of Dugoff tire model is made on two aspects: one is taking different tire/road friction coefficients for different magnitudes of slip and the other is employing the concept of friction ellipse. The proposed model is evaluated by comparison with the LuGre tire model. Although there are some discrepancies between the two models, the proposed combined-slip model is generally acceptable due to its simplicity and easiness to use. Extracting parameters from the coefficients of a Magic Formula tire model based on measured tire data, the proposed model is further evaluated by conducting a double lane change maneuver, and simulation ...

Application of Recursive Least Square Algorithm on Estimation of Vehicle Sideslip Angle and Road Friction

A recursive least square (RLS) algorithm for estimation of vehicle sideslip angle and road friction coefficient is proposed. The algorithm uses the information from sensors onboard vehicle and control inputs from the control logic and is intended to provide the essential information for active safety systems such as active steering, direct yaw moment control, or their combination. Based on a simple two-degree-of-freedom (DOF) vehicle model, the algorithm minimizes the squared errors between estimated lateral acceleration and yaw acceleration of the vehicle and their measured values. The algorithm also utilizes available control inputs such as active steering angle and wheel brake torques. The proposed algorithm is evaluated using an 8-DOF full vehicle simulation model including all essential nonlinearities and an integrated active front steering and direct yaw moment control on dry and slippery roads.

Motion-Based Energy Harvesting Devices for Railroad Applications

As the story goes, a wise railroad man once declared: Power is the king! Although he was referring to the motive power that we need to move freight, the same could be said about the availability of electrical power on railcars. This is mainly due to the fact that the onboard applications of many smart devices that can add to the efficiency of rail operation are hindered by the lack of availability of electrical power. In this paper, innovative solutions to provide a distributed source of electrical power for railroad onboard applications are presented. In a suspension of a railcar, mechanical energy is dissipated in dampers or wedges and, therefore, wasted in heat. Meant to be placed inside the coil springs of the suspension, the proposed vibration-based electromechanical systems are designed to harvest part of that wasted energy and turn it into useful electrical power. The energy produced is then conditioned and stored in commonly available batteries. The possibility of realizing the mechanical-to-electrical power conversion without any prior transformation of the mechanical input is first investigated. This aims to avoid inherent losses induced in such processes. The prototypes use an arrangement of magnets that moves linearly with the suspension inside one or several coils. The variable magnetic field thus created generates a voltage. The prototypes prove that it is possible to use a translational generator to provide enough power for recharging batteries under conditions commonly experienced in railcar operation. The second generation of prototypes investigates the idea of transforming the input translation from the suspension into rotation and then using a rotary generator. The advantage of developing such a concept is the possibility of including a gearbox to increase the generator speed of rotation. Maintaining high shaft speed is the key to harvest more power and reach higher efficiencies. The output power is improved even more by adding a mechanism that rotates the generator shaft in the same direction independently of how the suspension is moving (jounce or rebound). Both designs prove they can recharge batteries under commonly experienced conditions. But although the linear generator shows some limitations in terms of power (up to a few watts RMS), the rotary generator design demonstrates significantly higher efficiency and greater output power (40Watts RMS with a sine wave input of ±0.75in at 1Hz). The amount of generated power can be augmented by increasing the amplitude and/or the frequency of the input, customizing the generator, and bringing new improvements to the mechanical part of the system.Copyright

Optimal vehicle stability control design based on preview game theory concept

In this paper, vehicle stability is represented by a cooperative dynamic game such that its two agents (players), namely, the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the well-known Nash game theory to ensure optimal performance as well as robustness to disturbances. The common bicycle model is put into discrete form to develop the game equations of motion. To evaluate the control algorithm developed, a nonlinear vehicle model along with the combined-slip Pacejka tire model is used. The control algorithm is evaluated for a lane change maneuver, and the optimal set of steering angle and corrective yaw moment is calculated and fed to the test vehicle. The simulation results show that the optimal preview control algorithm can significantly reduce lateral velocity and yaw rate which all contribute to enhancing vehicle stability.

Estimation of the tyre–road maximum friction coefficient and slip slope based on a novel tyre model

In this article, a new approach to estimate the vehicle tyre forces, tyre–road maximum friction coefficient, and slip slope is presented. Contrary to the majority of the previous work on this subject, a new tyre model for the estimation of the tyre–road interface characterisation is proposed. First, the tyre model is built and compared with those of Pacejka, Dugoff, and one other tyre model. Then, based on a vehicle model that uses four degrees of freedom, an extended Kalman filter (EKF) method is designed to estimate the vehicle motion and tyre forces. The shortcomings of force estimation are discussed in this article. Based on the proposed tyre model and the improved force measurements, another EKF is implemented to estimate the tyre model parameters, including the maximum friction coefficient, slip slope, etc. The tyre forces are accurately obtained simultaneously. Finally, very promising results have been achieved for pure acceleration/braking for varying road conditions, both in pure steering and combined manoeuvre simulations.

Optimal VSC design based on Nash strategy for differential 2-player games

For optimal vehicle yaw stability control system development, inclusion of driver dynamics seems necessary. In this paper, a novel design approach is proposed for developing optimal solutions to vehicle stability control problems in the presence of the driver-in-the-loop steering models. The design concept is inspired by a Nash strategy for exactly known systems with more than two players. In the presented method, driver, controlling the steering wheel, and vehicle stability control unit, applying braking torques on the wheels, are defined as two dynamic players in a 2-player differential LQ game, and as a result, a novel control algorithm is developed. The results from a numerical simulation of a single lane change maneuver show the effectiveness of this controller over the common LQR control approach.